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TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Hill Cipher:
The 'HillCipher' class below implements the Hill Cipher algorithm which uses
modern linear algebra techniques to encode and decode text using an encryption
key matrix.
Algorithm:
Let the order of the encryption key be N (as it is a square matrix).
Your text is divided into batches of length N and converted to numerical vectors
by a simple mapping starting with A=0 and so on.
The key is then multiplied with the newly created batch vector to obtain the
encoded vector. After each multiplication modular 36 calculations are performed
on the vectors so as to bring the numbers between 0 and 36 and then mapped with
their corresponding alphanumerics.
While decrypting, the decrypting key is found which is the inverse of the
encrypting key modular 36. The same process is repeated for decrypting to get
the original message back.
Constraints:
The determinant of the encryption key matrix must be relatively prime w.r.t 36.
Note:
This implementation only considers alphanumerics in the text. If the length of
the text to be encrypted is not a multiple of the break key(the length of one
batch of letters), the last character of the text is added to the text until the
length of the text reaches a multiple of the break_key. So the text after
decrypting might be a little different than the original text.
References:
https://apprendre-en-ligne.net/crypto/hill/Hillciph.pdf
https://www.youtube.com/watch?v=kfmNeskzs2o
https://www.youtube.com/watch?v=4RhLNDqcjpA
"""
import string
import numpy
def greatest_common_divisor(a: int, b: int) -> int:
"""
>>> greatest_common_divisor(4, 8)
4
>>> greatest_common_divisor(8, 4)
4
>>> greatest_common_divisor(4, 7)
1
>>> greatest_common_divisor(0, 10)
10
"""
return b if a == 0 else greatest_common_divisor(b % a, a)
class HillCipher:
key_string = string.ascii_uppercase + string.digits
# This cipher takes alphanumerics into account
# i.e. a total of 36 characters
# take x and return x % len(key_string)
modulus = numpy.vectorize(lambda x: x % 36)
to_int = numpy.vectorize(lambda x: round(x))
def __init__(self, encrypt_key: int):
"""
encrypt_key is an NxN numpy array
"""
self.encrypt_key = self.modulus(encrypt_key) # mod36 calc's on the encrypt key
self.check_determinant() # validate the determinant of the encryption key
self.decrypt_key = None
self.break_key = encrypt_key.shape[0]
def replace_letters(self, letter: str) -> int:
"""
>>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
>>> hill_cipher.replace_letters('T')
19
>>> hill_cipher.replace_letters('0')
26
"""
return self.key_string.index(letter)
def replace_digits(self, num: int) -> str:
"""
>>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
>>> hill_cipher.replace_digits(19)
'T'
>>> hill_cipher.replace_digits(26)
'0'
"""
return self.key_string[round(num)]
def check_determinant(self) -> None:
"""
>>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
>>> hill_cipher.check_determinant()
"""
det = round(numpy.linalg.det(self.encrypt_key))
if det < 0:
det = det % len(self.key_string)
req_l = len(self.key_string)
if greatest_common_divisor(det, len(self.key_string)) != 1:
raise ValueError(
f"determinant modular {req_l} of encryption key({det}) is not co prime "
f"w.r.t {req_l}.\nTry another key."
)
def process_text(self, text: str) -> str:
"""
>>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
>>> hill_cipher.process_text('Testing Hill Cipher')
'TESTINGHILLCIPHERR'
>>> hill_cipher.process_text('hello')
'HELLOO'
"""
chars = [char for char in text.upper() if char in self.key_string]
last = chars[-1]
while len(chars) % self.break_key != 0:
chars.append(last)
return "".join(chars)
def encrypt(self, text: str) -> str:
"""
>>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
>>> hill_cipher.encrypt('testing hill cipher')
'WHXYJOLM9C6XT085LL'
>>> hill_cipher.encrypt('hello')
'85FF00'
"""
text = self.process_text(text.upper())
encrypted = ""
for i in range(0, len(text) - self.break_key + 1, self.break_key):
batch = text[i : i + self.break_key]
batch_vec = [self.replace_letters(char) for char in batch]
batch_vec = numpy.array([batch_vec]).T
batch_encrypted = self.modulus(self.encrypt_key.dot(batch_vec)).T.tolist()[
0
]
encrypted_batch = "".join(
self.replace_digits(num) for num in batch_encrypted
)
encrypted += encrypted_batch
return encrypted
def make_decrypt_key(self):
"""
>>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
>>> hill_cipher.make_decrypt_key()
array([[ 6, 25],
[ 5, 26]])
"""
det = round(numpy.linalg.det(self.encrypt_key))
if det < 0:
det = det % len(self.key_string)
det_inv = None
for i in range(len(self.key_string)):
if (det * i) % len(self.key_string) == 1:
det_inv = i
break
inv_key = (
det_inv
* numpy.linalg.det(self.encrypt_key)
* numpy.linalg.inv(self.encrypt_key)
)
return self.to_int(self.modulus(inv_key))
def decrypt(self, text: str) -> str:
"""
>>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
>>> hill_cipher.decrypt('WHXYJOLM9C6XT085LL')
'TESTINGHILLCIPHERR'
>>> hill_cipher.decrypt('85FF00')
'HELLOO'
"""
self.decrypt_key = self.make_decrypt_key()
text = self.process_text(text.upper())
decrypted = ""
for i in range(0, len(text) - self.break_key + 1, self.break_key):
batch = text[i : i + self.break_key]
batch_vec = [self.replace_letters(char) for char in batch]
batch_vec = numpy.array([batch_vec]).T
batch_decrypted = self.modulus(self.decrypt_key.dot(batch_vec)).T.tolist()[
0
]
decrypted_batch = "".join(
self.replace_digits(num) for num in batch_decrypted
)
decrypted += decrypted_batch
return decrypted
def main():
N = int(input("Enter the order of the encryption key: "))
hill_matrix = []
print("Enter each row of the encryption key with space separated integers")
for i in range(N):
row = [int(x) for x in input().split()]
hill_matrix.append(row)
hc = HillCipher(numpy.array(hill_matrix))
print("Would you like to encrypt or decrypt some text? (1 or 2)")
option = input("\n1. Encrypt\n2. Decrypt\n")
if option == "1":
text_e = input("What text would you like to encrypt?: ")
print("Your encrypted text is:")
print(hc.encrypt(text_e))
elif option == "2":
text_d = input("What text would you like to decrypt?: ")
print("Your decrypted text is:")
print(hc.decrypt(text_d))
if __name__ == "__main__":
import doctest
doctest.testmod()
main()
| """
Hill Cipher:
The 'HillCipher' class below implements the Hill Cipher algorithm which uses
modern linear algebra techniques to encode and decode text using an encryption
key matrix.
Algorithm:
Let the order of the encryption key be N (as it is a square matrix).
Your text is divided into batches of length N and converted to numerical vectors
by a simple mapping starting with A=0 and so on.
The key is then multiplied with the newly created batch vector to obtain the
encoded vector. After each multiplication modular 36 calculations are performed
on the vectors so as to bring the numbers between 0 and 36 and then mapped with
their corresponding alphanumerics.
While decrypting, the decrypting key is found which is the inverse of the
encrypting key modular 36. The same process is repeated for decrypting to get
the original message back.
Constraints:
The determinant of the encryption key matrix must be relatively prime w.r.t 36.
Note:
This implementation only considers alphanumerics in the text. If the length of
the text to be encrypted is not a multiple of the break key(the length of one
batch of letters), the last character of the text is added to the text until the
length of the text reaches a multiple of the break_key. So the text after
decrypting might be a little different than the original text.
References:
https://apprendre-en-ligne.net/crypto/hill/Hillciph.pdf
https://www.youtube.com/watch?v=kfmNeskzs2o
https://www.youtube.com/watch?v=4RhLNDqcjpA
"""
import string
import numpy
def greatest_common_divisor(a: int, b: int) -> int:
"""
>>> greatest_common_divisor(4, 8)
4
>>> greatest_common_divisor(8, 4)
4
>>> greatest_common_divisor(4, 7)
1
>>> greatest_common_divisor(0, 10)
10
"""
return b if a == 0 else greatest_common_divisor(b % a, a)
class HillCipher:
key_string = string.ascii_uppercase + string.digits
# This cipher takes alphanumerics into account
# i.e. a total of 36 characters
# take x and return x % len(key_string)
modulus = numpy.vectorize(lambda x: x % 36)
to_int = numpy.vectorize(lambda x: round(x))
def __init__(self, encrypt_key: int):
"""
encrypt_key is an NxN numpy array
"""
self.encrypt_key = self.modulus(encrypt_key) # mod36 calc's on the encrypt key
self.check_determinant() # validate the determinant of the encryption key
self.decrypt_key = None
self.break_key = encrypt_key.shape[0]
def replace_letters(self, letter: str) -> int:
"""
>>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
>>> hill_cipher.replace_letters('T')
19
>>> hill_cipher.replace_letters('0')
26
"""
return self.key_string.index(letter)
def replace_digits(self, num: int) -> str:
"""
>>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
>>> hill_cipher.replace_digits(19)
'T'
>>> hill_cipher.replace_digits(26)
'0'
"""
return self.key_string[round(num)]
def check_determinant(self) -> None:
"""
>>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
>>> hill_cipher.check_determinant()
"""
det = round(numpy.linalg.det(self.encrypt_key))
if det < 0:
det = det % len(self.key_string)
req_l = len(self.key_string)
if greatest_common_divisor(det, len(self.key_string)) != 1:
raise ValueError(
f"determinant modular {req_l} of encryption key({det}) is not co prime "
f"w.r.t {req_l}.\nTry another key."
)
def process_text(self, text: str) -> str:
"""
>>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
>>> hill_cipher.process_text('Testing Hill Cipher')
'TESTINGHILLCIPHERR'
>>> hill_cipher.process_text('hello')
'HELLOO'
"""
chars = [char for char in text.upper() if char in self.key_string]
last = chars[-1]
while len(chars) % self.break_key != 0:
chars.append(last)
return "".join(chars)
def encrypt(self, text: str) -> str:
"""
>>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
>>> hill_cipher.encrypt('testing hill cipher')
'WHXYJOLM9C6XT085LL'
>>> hill_cipher.encrypt('hello')
'85FF00'
"""
text = self.process_text(text.upper())
encrypted = ""
for i in range(0, len(text) - self.break_key + 1, self.break_key):
batch = text[i : i + self.break_key]
batch_vec = [self.replace_letters(char) for char in batch]
batch_vec = numpy.array([batch_vec]).T
batch_encrypted = self.modulus(self.encrypt_key.dot(batch_vec)).T.tolist()[
0
]
encrypted_batch = "".join(
self.replace_digits(num) for num in batch_encrypted
)
encrypted += encrypted_batch
return encrypted
def make_decrypt_key(self):
"""
>>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
>>> hill_cipher.make_decrypt_key()
array([[ 6, 25],
[ 5, 26]])
"""
det = round(numpy.linalg.det(self.encrypt_key))
if det < 0:
det = det % len(self.key_string)
det_inv = None
for i in range(len(self.key_string)):
if (det * i) % len(self.key_string) == 1:
det_inv = i
break
inv_key = (
det_inv
* numpy.linalg.det(self.encrypt_key)
* numpy.linalg.inv(self.encrypt_key)
)
return self.to_int(self.modulus(inv_key))
def decrypt(self, text: str) -> str:
"""
>>> hill_cipher = HillCipher(numpy.array([[2, 5], [1, 6]]))
>>> hill_cipher.decrypt('WHXYJOLM9C6XT085LL')
'TESTINGHILLCIPHERR'
>>> hill_cipher.decrypt('85FF00')
'HELLOO'
"""
self.decrypt_key = self.make_decrypt_key()
text = self.process_text(text.upper())
decrypted = ""
for i in range(0, len(text) - self.break_key + 1, self.break_key):
batch = text[i : i + self.break_key]
batch_vec = [self.replace_letters(char) for char in batch]
batch_vec = numpy.array([batch_vec]).T
batch_decrypted = self.modulus(self.decrypt_key.dot(batch_vec)).T.tolist()[
0
]
decrypted_batch = "".join(
self.replace_digits(num) for num in batch_decrypted
)
decrypted += decrypted_batch
return decrypted
def main():
N = int(input("Enter the order of the encryption key: "))
hill_matrix = []
print("Enter each row of the encryption key with space separated integers")
for i in range(N):
row = [int(x) for x in input().split()]
hill_matrix.append(row)
hc = HillCipher(numpy.array(hill_matrix))
print("Would you like to encrypt or decrypt some text? (1 or 2)")
option = input("\n1. Encrypt\n2. Decrypt\n")
if option == "1":
text_e = input("What text would you like to encrypt?: ")
print("Your encrypted text is:")
print(hc.encrypt(text_e))
elif option == "2":
text_d = input("What text would you like to decrypt?: ")
print("Your decrypted text is:")
print(hc.decrypt(text_d))
if __name__ == "__main__":
import doctest
doctest.testmod()
main()
| -1 |
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
References: wikipedia:square free number
python/black : True
flake8 : True
"""
from __future__ import annotations
def is_square_free(factors: list[int]) -> bool:
"""
# doctest: +NORMALIZE_WHITESPACE
This functions takes a list of prime factors as input.
returns True if the factors are square free.
>>> is_square_free([1, 1, 2, 3, 4])
False
These are wrong but should return some value
it simply checks for repition in the numbers.
>>> is_square_free([1, 3, 4, 'sd', 0.0])
True
>>> is_square_free([1, 0.5, 2, 0.0])
True
>>> is_square_free([1, 2, 2, 5])
False
>>> is_square_free('asd')
True
>>> is_square_free(24)
Traceback (most recent call last):
...
TypeError: 'int' object is not iterable
"""
return len(set(factors)) == len(factors)
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
References: wikipedia:square free number
python/black : True
flake8 : True
"""
from __future__ import annotations
def is_square_free(factors: list[int]) -> bool:
"""
# doctest: +NORMALIZE_WHITESPACE
This functions takes a list of prime factors as input.
returns True if the factors are square free.
>>> is_square_free([1, 1, 2, 3, 4])
False
These are wrong but should return some value
it simply checks for repition in the numbers.
>>> is_square_free([1, 3, 4, 'sd', 0.0])
True
>>> is_square_free([1, 0.5, 2, 0.0])
True
>>> is_square_free([1, 2, 2, 5])
False
>>> is_square_free('asd')
True
>>> is_square_free(24)
Traceback (most recent call last):
...
TypeError: 'int' object is not iterable
"""
return len(set(factors)) == len(factors)
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 203: https://projecteuler.net/problem=203
The binomial coefficients (n k) can be arranged in triangular form, Pascal's
triangle, like this:
1
1 1
1 2 1
1 3 3 1
1 4 6 4 1
1 5 10 10 5 1
1 6 15 20 15 6 1
1 7 21 35 35 21 7 1
.........
It can be seen that the first eight rows of Pascal's triangle contain twelve
distinct numbers: 1, 2, 3, 4, 5, 6, 7, 10, 15, 20, 21 and 35.
A positive integer n is called squarefree if no square of a prime divides n.
Of the twelve distinct numbers in the first eight rows of Pascal's triangle,
all except 4 and 20 are squarefree. The sum of the distinct squarefree numbers
in the first eight rows is 105.
Find the sum of the distinct squarefree numbers in the first 51 rows of
Pascal's triangle.
References:
- https://en.wikipedia.org/wiki/Pascal%27s_triangle
"""
import math
from typing import List, Set
def get_pascal_triangle_unique_coefficients(depth: int) -> Set[int]:
"""
Returns the unique coefficients of a Pascal's triangle of depth "depth".
The coefficients of this triangle are symmetric. A further improvement to this
method could be to calculate the coefficients once per level. Nonetheless,
the current implementation is fast enough for the original problem.
>>> get_pascal_triangle_unique_coefficients(1)
{1}
>>> get_pascal_triangle_unique_coefficients(2)
{1}
>>> get_pascal_triangle_unique_coefficients(3)
{1, 2}
>>> get_pascal_triangle_unique_coefficients(8)
{1, 2, 3, 4, 5, 6, 7, 35, 10, 15, 20, 21}
"""
coefficients = {1}
previous_coefficients = [1]
for step in range(2, depth + 1):
coefficients_begins_one = previous_coefficients + [0]
coefficients_ends_one = [0] + previous_coefficients
previous_coefficients = []
for x, y in zip(coefficients_begins_one, coefficients_ends_one):
coefficients.add(x + y)
previous_coefficients.append(x + y)
return coefficients
def get_primes_squared(max_number: int) -> List[int]:
"""
Calculates all primes between 2 and round(sqrt(max_number)) and returns
them squared up.
>>> get_primes_squared(2)
[]
>>> get_primes_squared(4)
[4]
>>> get_primes_squared(10)
[4, 9]
>>> get_primes_squared(100)
[4, 9, 25, 49]
"""
max_prime = round(math.sqrt(max_number))
non_primes = set()
primes = []
for num in range(2, max_prime + 1):
if num in non_primes:
continue
counter = 2
while num * counter <= max_prime:
non_primes.add(num * counter)
counter += 1
primes.append(num ** 2)
return primes
def get_squared_primes_to_use(
num_to_look: int, squared_primes: List[int], previous_index: int
) -> int:
"""
Returns an int indicating the last index on which squares of primes
in primes are lower than num_to_look.
This method supposes that squared_primes is sorted in ascending order and that
each num_to_look is provided in ascending order as well. Under these
assumptions, it needs a previous_index parameter that tells what was
the index returned by the method for the previous num_to_look.
If all the elements in squared_primes are greater than num_to_look, then the
method returns -1.
>>> get_squared_primes_to_use(1, [4, 9, 16, 25], 0)
-1
>>> get_squared_primes_to_use(4, [4, 9, 16, 25], 0)
1
>>> get_squared_primes_to_use(16, [4, 9, 16, 25], 1)
3
"""
idx = max(previous_index, 0)
while idx < len(squared_primes) and squared_primes[idx] <= num_to_look:
idx += 1
if idx == 0 and squared_primes[idx] > num_to_look:
return -1
if idx == len(squared_primes) and squared_primes[-1] > num_to_look:
return -1
return idx
def get_squarefree(
unique_coefficients: Set[int], squared_primes: List[int]
) -> Set[int]:
"""
Calculates the squarefree numbers inside unique_coefficients given a
list of square of primes.
Based on the definition of a non-squarefree number, then any non-squarefree
n can be decomposed as n = p*p*r, where p is positive prime number and r
is a positive integer.
Under the previous formula, any coefficient that is lower than p*p is
squarefree as r cannot be negative. On the contrary, if any r exists such
that n = p*p*r, then the number is non-squarefree.
>>> get_squarefree({1}, [])
set()
>>> get_squarefree({1, 2}, [])
set()
>>> get_squarefree({1, 2, 3, 4, 5, 6, 7, 35, 10, 15, 20, 21}, [4, 9, 25])
{1, 2, 3, 5, 6, 7, 35, 10, 15, 21}
"""
if len(squared_primes) == 0:
return set()
non_squarefrees = set()
prime_squared_idx = 0
for num in sorted(unique_coefficients):
prime_squared_idx = get_squared_primes_to_use(
num, squared_primes, prime_squared_idx
)
if prime_squared_idx == -1:
continue
if any(num % prime == 0 for prime in squared_primes[:prime_squared_idx]):
non_squarefrees.add(num)
return unique_coefficients.difference(non_squarefrees)
def solution(n: int = 51) -> int:
"""
Returns the sum of squarefrees for a given Pascal's Triangle of depth n.
>>> solution(1)
0
>>> solution(8)
105
>>> solution(9)
175
"""
unique_coefficients = get_pascal_triangle_unique_coefficients(n)
primes = get_primes_squared(max(unique_coefficients))
squarefrees = get_squarefree(unique_coefficients, primes)
return sum(squarefrees)
if __name__ == "__main__":
print(f"{solution() = }")
| """
Project Euler Problem 203: https://projecteuler.net/problem=203
The binomial coefficients (n k) can be arranged in triangular form, Pascal's
triangle, like this:
1
1 1
1 2 1
1 3 3 1
1 4 6 4 1
1 5 10 10 5 1
1 6 15 20 15 6 1
1 7 21 35 35 21 7 1
.........
It can be seen that the first eight rows of Pascal's triangle contain twelve
distinct numbers: 1, 2, 3, 4, 5, 6, 7, 10, 15, 20, 21 and 35.
A positive integer n is called squarefree if no square of a prime divides n.
Of the twelve distinct numbers in the first eight rows of Pascal's triangle,
all except 4 and 20 are squarefree. The sum of the distinct squarefree numbers
in the first eight rows is 105.
Find the sum of the distinct squarefree numbers in the first 51 rows of
Pascal's triangle.
References:
- https://en.wikipedia.org/wiki/Pascal%27s_triangle
"""
import math
from typing import List, Set
def get_pascal_triangle_unique_coefficients(depth: int) -> Set[int]:
"""
Returns the unique coefficients of a Pascal's triangle of depth "depth".
The coefficients of this triangle are symmetric. A further improvement to this
method could be to calculate the coefficients once per level. Nonetheless,
the current implementation is fast enough for the original problem.
>>> get_pascal_triangle_unique_coefficients(1)
{1}
>>> get_pascal_triangle_unique_coefficients(2)
{1}
>>> get_pascal_triangle_unique_coefficients(3)
{1, 2}
>>> get_pascal_triangle_unique_coefficients(8)
{1, 2, 3, 4, 5, 6, 7, 35, 10, 15, 20, 21}
"""
coefficients = {1}
previous_coefficients = [1]
for step in range(2, depth + 1):
coefficients_begins_one = previous_coefficients + [0]
coefficients_ends_one = [0] + previous_coefficients
previous_coefficients = []
for x, y in zip(coefficients_begins_one, coefficients_ends_one):
coefficients.add(x + y)
previous_coefficients.append(x + y)
return coefficients
def get_primes_squared(max_number: int) -> List[int]:
"""
Calculates all primes between 2 and round(sqrt(max_number)) and returns
them squared up.
>>> get_primes_squared(2)
[]
>>> get_primes_squared(4)
[4]
>>> get_primes_squared(10)
[4, 9]
>>> get_primes_squared(100)
[4, 9, 25, 49]
"""
max_prime = round(math.sqrt(max_number))
non_primes = set()
primes = []
for num in range(2, max_prime + 1):
if num in non_primes:
continue
counter = 2
while num * counter <= max_prime:
non_primes.add(num * counter)
counter += 1
primes.append(num ** 2)
return primes
def get_squared_primes_to_use(
num_to_look: int, squared_primes: List[int], previous_index: int
) -> int:
"""
Returns an int indicating the last index on which squares of primes
in primes are lower than num_to_look.
This method supposes that squared_primes is sorted in ascending order and that
each num_to_look is provided in ascending order as well. Under these
assumptions, it needs a previous_index parameter that tells what was
the index returned by the method for the previous num_to_look.
If all the elements in squared_primes are greater than num_to_look, then the
method returns -1.
>>> get_squared_primes_to_use(1, [4, 9, 16, 25], 0)
-1
>>> get_squared_primes_to_use(4, [4, 9, 16, 25], 0)
1
>>> get_squared_primes_to_use(16, [4, 9, 16, 25], 1)
3
"""
idx = max(previous_index, 0)
while idx < len(squared_primes) and squared_primes[idx] <= num_to_look:
idx += 1
if idx == 0 and squared_primes[idx] > num_to_look:
return -1
if idx == len(squared_primes) and squared_primes[-1] > num_to_look:
return -1
return idx
def get_squarefree(
unique_coefficients: Set[int], squared_primes: List[int]
) -> Set[int]:
"""
Calculates the squarefree numbers inside unique_coefficients given a
list of square of primes.
Based on the definition of a non-squarefree number, then any non-squarefree
n can be decomposed as n = p*p*r, where p is positive prime number and r
is a positive integer.
Under the previous formula, any coefficient that is lower than p*p is
squarefree as r cannot be negative. On the contrary, if any r exists such
that n = p*p*r, then the number is non-squarefree.
>>> get_squarefree({1}, [])
set()
>>> get_squarefree({1, 2}, [])
set()
>>> get_squarefree({1, 2, 3, 4, 5, 6, 7, 35, 10, 15, 20, 21}, [4, 9, 25])
{1, 2, 3, 5, 6, 7, 35, 10, 15, 21}
"""
if len(squared_primes) == 0:
return set()
non_squarefrees = set()
prime_squared_idx = 0
for num in sorted(unique_coefficients):
prime_squared_idx = get_squared_primes_to_use(
num, squared_primes, prime_squared_idx
)
if prime_squared_idx == -1:
continue
if any(num % prime == 0 for prime in squared_primes[:prime_squared_idx]):
non_squarefrees.add(num)
return unique_coefficients.difference(non_squarefrees)
def solution(n: int = 51) -> int:
"""
Returns the sum of squarefrees for a given Pascal's Triangle of depth n.
>>> solution(1)
0
>>> solution(8)
105
>>> solution(9)
175
"""
unique_coefficients = get_pascal_triangle_unique_coefficients(n)
primes = get_primes_squared(max(unique_coefficients))
squarefrees = get_squarefree(unique_coefficients, primes)
return sum(squarefrees)
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
This is a pure Python implementation of the merge-insertion sort algorithm
Source: https://en.wikipedia.org/wiki/Merge-insertion_sort
For doctests run following command:
python3 -m doctest -v merge_insertion_sort.py
or
python -m doctest -v merge_insertion_sort.py
For manual testing run:
python3 merge_insertion_sort.py
"""
from __future__ import annotations
def merge_insertion_sort(collection: list[int]) -> list[int]:
"""Pure implementation of merge-insertion sort algorithm in Python
:param collection: some mutable ordered collection with heterogeneous
comparable items inside
:return: the same collection ordered by ascending
Examples:
>>> merge_insertion_sort([0, 5, 3, 2, 2])
[0, 2, 2, 3, 5]
>>> merge_insertion_sort([99])
[99]
>>> merge_insertion_sort([-2, -5, -45])
[-45, -5, -2]
"""
def binary_search_insertion(sorted_list, item):
left = 0
right = len(sorted_list) - 1
while left <= right:
middle = (left + right) // 2
if left == right:
if sorted_list[middle] < item:
left = middle + 1
break
elif sorted_list[middle] < item:
left = middle + 1
else:
right = middle - 1
sorted_list.insert(left, item)
return sorted_list
def sortlist_2d(list_2d):
def merge(left, right):
result = []
while left and right:
if left[0][0] < right[0][0]:
result.append(left.pop(0))
else:
result.append(right.pop(0))
return result + left + right
length = len(list_2d)
if length <= 1:
return list_2d
middle = length // 2
return merge(sortlist_2d(list_2d[:middle]), sortlist_2d(list_2d[middle:]))
if len(collection) <= 1:
return collection
"""
Group the items into two pairs, and leave one element if there is a last odd item.
Example: [999, 100, 75, 40, 10000]
-> [999, 100], [75, 40]. Leave 10000.
"""
two_paired_list = []
has_last_odd_item = False
for i in range(0, len(collection), 2):
if i == len(collection) - 1:
has_last_odd_item = True
else:
"""
Sort two-pairs in each groups.
Example: [999, 100], [75, 40]
-> [100, 999], [40, 75]
"""
if collection[i] < collection[i + 1]:
two_paired_list.append([collection[i], collection[i + 1]])
else:
two_paired_list.append([collection[i + 1], collection[i]])
"""
Sort two_paired_list.
Example: [100, 999], [40, 75]
-> [40, 75], [100, 999]
"""
sorted_list_2d = sortlist_2d(two_paired_list)
"""
40 < 100 is sure because it has already been sorted.
Generate the sorted_list of them so that you can avoid unnecessary comparison.
Example:
group0 group1
40 100
75 999
->
group0 group1
[40, 100]
75 999
"""
result = [i[0] for i in sorted_list_2d]
"""
100 < 999 is sure because it has already been sorted.
Put 999 in last of the sorted_list so that you can avoid unnecessary comparison.
Example:
group0 group1
[40, 100]
75 999
->
group0 group1
[40, 100, 999]
75
"""
result.append(sorted_list_2d[-1][1])
"""
Insert the last odd item left if there is.
Example:
group0 group1
[40, 100, 999]
75
->
group0 group1
[40, 100, 999, 10000]
75
"""
if has_last_odd_item:
pivot = collection[-1]
result = binary_search_insertion(result, pivot)
"""
Insert the remaining items.
In this case, 40 < 75 is sure because it has already been sorted.
Therefore, you only need to insert 75 into [100, 999, 10000],
so that you can avoid unnecessary comparison.
Example:
group0 group1
[40, 100, 999, 10000]
^ You don't need to compare with this as 40 < 75 is already sure.
75
->
[40, 75, 100, 999, 10000]
"""
is_last_odd_item_inserted_before_this_index = False
for i in range(len(sorted_list_2d) - 1):
if result[i] == collection[-i]:
is_last_odd_item_inserted_before_this_index = True
pivot = sorted_list_2d[i][1]
# If last_odd_item is inserted before the item's index,
# you should forward index one more.
if is_last_odd_item_inserted_before_this_index:
result = result[: i + 2] + binary_search_insertion(result[i + 2 :], pivot)
else:
result = result[: i + 1] + binary_search_insertion(result[i + 1 :], pivot)
return result
if __name__ == "__main__":
user_input = input("Enter numbers separated by a comma:\n").strip()
unsorted = [int(item) for item in user_input.split(",")]
print(merge_insertion_sort(unsorted))
| """
This is a pure Python implementation of the merge-insertion sort algorithm
Source: https://en.wikipedia.org/wiki/Merge-insertion_sort
For doctests run following command:
python3 -m doctest -v merge_insertion_sort.py
or
python -m doctest -v merge_insertion_sort.py
For manual testing run:
python3 merge_insertion_sort.py
"""
from __future__ import annotations
def merge_insertion_sort(collection: list[int]) -> list[int]:
"""Pure implementation of merge-insertion sort algorithm in Python
:param collection: some mutable ordered collection with heterogeneous
comparable items inside
:return: the same collection ordered by ascending
Examples:
>>> merge_insertion_sort([0, 5, 3, 2, 2])
[0, 2, 2, 3, 5]
>>> merge_insertion_sort([99])
[99]
>>> merge_insertion_sort([-2, -5, -45])
[-45, -5, -2]
"""
def binary_search_insertion(sorted_list, item):
left = 0
right = len(sorted_list) - 1
while left <= right:
middle = (left + right) // 2
if left == right:
if sorted_list[middle] < item:
left = middle + 1
break
elif sorted_list[middle] < item:
left = middle + 1
else:
right = middle - 1
sorted_list.insert(left, item)
return sorted_list
def sortlist_2d(list_2d):
def merge(left, right):
result = []
while left and right:
if left[0][0] < right[0][0]:
result.append(left.pop(0))
else:
result.append(right.pop(0))
return result + left + right
length = len(list_2d)
if length <= 1:
return list_2d
middle = length // 2
return merge(sortlist_2d(list_2d[:middle]), sortlist_2d(list_2d[middle:]))
if len(collection) <= 1:
return collection
"""
Group the items into two pairs, and leave one element if there is a last odd item.
Example: [999, 100, 75, 40, 10000]
-> [999, 100], [75, 40]. Leave 10000.
"""
two_paired_list = []
has_last_odd_item = False
for i in range(0, len(collection), 2):
if i == len(collection) - 1:
has_last_odd_item = True
else:
"""
Sort two-pairs in each groups.
Example: [999, 100], [75, 40]
-> [100, 999], [40, 75]
"""
if collection[i] < collection[i + 1]:
two_paired_list.append([collection[i], collection[i + 1]])
else:
two_paired_list.append([collection[i + 1], collection[i]])
"""
Sort two_paired_list.
Example: [100, 999], [40, 75]
-> [40, 75], [100, 999]
"""
sorted_list_2d = sortlist_2d(two_paired_list)
"""
40 < 100 is sure because it has already been sorted.
Generate the sorted_list of them so that you can avoid unnecessary comparison.
Example:
group0 group1
40 100
75 999
->
group0 group1
[40, 100]
75 999
"""
result = [i[0] for i in sorted_list_2d]
"""
100 < 999 is sure because it has already been sorted.
Put 999 in last of the sorted_list so that you can avoid unnecessary comparison.
Example:
group0 group1
[40, 100]
75 999
->
group0 group1
[40, 100, 999]
75
"""
result.append(sorted_list_2d[-1][1])
"""
Insert the last odd item left if there is.
Example:
group0 group1
[40, 100, 999]
75
->
group0 group1
[40, 100, 999, 10000]
75
"""
if has_last_odd_item:
pivot = collection[-1]
result = binary_search_insertion(result, pivot)
"""
Insert the remaining items.
In this case, 40 < 75 is sure because it has already been sorted.
Therefore, you only need to insert 75 into [100, 999, 10000],
so that you can avoid unnecessary comparison.
Example:
group0 group1
[40, 100, 999, 10000]
^ You don't need to compare with this as 40 < 75 is already sure.
75
->
[40, 75, 100, 999, 10000]
"""
is_last_odd_item_inserted_before_this_index = False
for i in range(len(sorted_list_2d) - 1):
if result[i] == collection[-i]:
is_last_odd_item_inserted_before_this_index = True
pivot = sorted_list_2d[i][1]
# If last_odd_item is inserted before the item's index,
# you should forward index one more.
if is_last_odd_item_inserted_before_this_index:
result = result[: i + 2] + binary_search_insertion(result[i + 2 :], pivot)
else:
result = result[: i + 1] + binary_search_insertion(result[i + 1 :], pivot)
return result
if __name__ == "__main__":
user_input = input("Enter numbers separated by a comma:\n").strip()
unsorted = [int(item) for item in user_input.split(",")]
print(merge_insertion_sort(unsorted))
| -1 |
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
The Fibonacci sequence is defined by the recurrence relation:
Fn = Fn−1 + Fn−2, where F1 = 1 and F2 = 1.
Hence the first 12 terms will be:
F1 = 1
F2 = 1
F3 = 2
F4 = 3
F5 = 5
F6 = 8
F7 = 13
F8 = 21
F9 = 34
F10 = 55
F11 = 89
F12 = 144
The 12th term, F12, is the first term to contain three digits.
What is the index of the first term in the Fibonacci sequence to contain 1000
digits?
"""
def fibonacci(n: int) -> int:
"""
Computes the Fibonacci number for input n by iterating through n numbers
and creating an array of ints using the Fibonacci formula.
Returns the nth element of the array.
>>> fibonacci(2)
1
>>> fibonacci(3)
2
>>> fibonacci(5)
5
>>> fibonacci(10)
55
>>> fibonacci(12)
144
"""
if n == 1 or type(n) is not int:
return 0
elif n == 2:
return 1
else:
sequence = [0, 1]
for i in range(2, n + 1):
sequence.append(sequence[i - 1] + sequence[i - 2])
return sequence[n]
def fibonacci_digits_index(n: int) -> int:
"""
Computes incrementing Fibonacci numbers starting from 3 until the length
of the resulting Fibonacci result is the input value n. Returns the term
of the Fibonacci sequence where this occurs.
>>> fibonacci_digits_index(1000)
4782
>>> fibonacci_digits_index(100)
476
>>> fibonacci_digits_index(50)
237
>>> fibonacci_digits_index(3)
12
"""
digits = 0
index = 2
while digits < n:
index += 1
digits = len(str(fibonacci(index)))
return index
def solution(n: int = 1000) -> int:
"""
Returns the index of the first term in the Fibonacci sequence to contain
n digits.
>>> solution(1000)
4782
>>> solution(100)
476
>>> solution(50)
237
>>> solution(3)
12
"""
return fibonacci_digits_index(n)
if __name__ == "__main__":
print(solution(int(str(input()).strip())))
| """
The Fibonacci sequence is defined by the recurrence relation:
Fn = Fn−1 + Fn−2, where F1 = 1 and F2 = 1.
Hence the first 12 terms will be:
F1 = 1
F2 = 1
F3 = 2
F4 = 3
F5 = 5
F6 = 8
F7 = 13
F8 = 21
F9 = 34
F10 = 55
F11 = 89
F12 = 144
The 12th term, F12, is the first term to contain three digits.
What is the index of the first term in the Fibonacci sequence to contain 1000
digits?
"""
def fibonacci(n: int) -> int:
"""
Computes the Fibonacci number for input n by iterating through n numbers
and creating an array of ints using the Fibonacci formula.
Returns the nth element of the array.
>>> fibonacci(2)
1
>>> fibonacci(3)
2
>>> fibonacci(5)
5
>>> fibonacci(10)
55
>>> fibonacci(12)
144
"""
if n == 1 or type(n) is not int:
return 0
elif n == 2:
return 1
else:
sequence = [0, 1]
for i in range(2, n + 1):
sequence.append(sequence[i - 1] + sequence[i - 2])
return sequence[n]
def fibonacci_digits_index(n: int) -> int:
"""
Computes incrementing Fibonacci numbers starting from 3 until the length
of the resulting Fibonacci result is the input value n. Returns the term
of the Fibonacci sequence where this occurs.
>>> fibonacci_digits_index(1000)
4782
>>> fibonacci_digits_index(100)
476
>>> fibonacci_digits_index(50)
237
>>> fibonacci_digits_index(3)
12
"""
digits = 0
index = 2
while digits < n:
index += 1
digits = len(str(fibonacci(index)))
return index
def solution(n: int = 1000) -> int:
"""
Returns the index of the first term in the Fibonacci sequence to contain
n digits.
>>> solution(1000)
4782
>>> solution(100)
476
>>> solution(50)
237
>>> solution(3)
12
"""
return fibonacci_digits_index(n)
if __name__ == "__main__":
print(solution(int(str(input()).strip())))
| -1 |
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
This algorithm helps you to swap cases.
User will give input and then program will perform swap cases.
In other words, convert all lowercase letters to uppercase letters and vice versa.
For example:
1. Please input sentence: Algorithm.Python@89
aLGORITHM.pYTHON@89
2. Please input sentence: github.com/mayur200
GITHUB.COM/MAYUR200
"""
def swap_case(sentence: str) -> str:
"""
This function will convert all lowercase letters to uppercase letters
and vice versa.
>>> swap_case('Algorithm.Python@89')
'aLGORITHM.pYTHON@89'
"""
new_string = ""
for char in sentence:
if char.isupper():
new_string += char.lower()
elif char.islower():
new_string += char.upper()
else:
new_string += char
return new_string
if __name__ == "__main__":
print(swap_case(input("Please input sentence: ")))
| """
This algorithm helps you to swap cases.
User will give input and then program will perform swap cases.
In other words, convert all lowercase letters to uppercase letters and vice versa.
For example:
1. Please input sentence: Algorithm.Python@89
aLGORITHM.pYTHON@89
2. Please input sentence: github.com/mayur200
GITHUB.COM/MAYUR200
"""
def swap_case(sentence: str) -> str:
"""
This function will convert all lowercase letters to uppercase letters
and vice versa.
>>> swap_case('Algorithm.Python@89')
'aLGORITHM.pYTHON@89'
"""
new_string = ""
for char in sentence:
if char.isupper():
new_string += char.lower()
elif char.islower():
new_string += char.upper()
else:
new_string += char
return new_string
if __name__ == "__main__":
print(swap_case(input("Please input sentence: ")))
| -1 |
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| import math
from timeit import timeit
def num_digits(n: int) -> int:
"""
Find the number of digits in a number.
>>> num_digits(12345)
5
>>> num_digits(123)
3
>>> num_digits(0)
1
>>> num_digits(-1)
1
>>> num_digits(-123456)
6
"""
digits = 0
n = abs(n)
while True:
n = n // 10
digits += 1
if n == 0:
break
return digits
def num_digits_fast(n: int) -> int:
"""
Find the number of digits in a number.
abs() is used as logarithm for negative numbers is not defined.
>>> num_digits_fast(12345)
5
>>> num_digits_fast(123)
3
>>> num_digits_fast(0)
1
>>> num_digits_fast(-1)
1
>>> num_digits_fast(-123456)
6
"""
return 1 if n == 0 else math.floor(math.log(abs(n), 10) + 1)
def num_digits_faster(n: int) -> int:
"""
Find the number of digits in a number.
abs() is used for negative numbers
>>> num_digits_faster(12345)
5
>>> num_digits_faster(123)
3
>>> num_digits_faster(0)
1
>>> num_digits_faster(-1)
1
>>> num_digits_faster(-123456)
6
"""
return len(str(abs(n)))
def benchmark() -> None:
"""
Benchmark code for comparing 3 functions,
with 3 different length int values.
"""
print("\nFor small_num = ", small_num, ":")
print(
"> num_digits()",
"\t\tans =",
num_digits(small_num),
"\ttime =",
timeit("z.num_digits(z.small_num)", setup="import __main__ as z"),
"seconds",
)
print(
"> num_digits_fast()",
"\tans =",
num_digits_fast(small_num),
"\ttime =",
timeit("z.num_digits_fast(z.small_num)", setup="import __main__ as z"),
"seconds",
)
print(
"> num_digits_faster()",
"\tans =",
num_digits_faster(small_num),
"\ttime =",
timeit("z.num_digits_faster(z.small_num)", setup="import __main__ as z"),
"seconds",
)
print("\nFor medium_num = ", medium_num, ":")
print(
"> num_digits()",
"\t\tans =",
num_digits(medium_num),
"\ttime =",
timeit("z.num_digits(z.medium_num)", setup="import __main__ as z"),
"seconds",
)
print(
"> num_digits_fast()",
"\tans =",
num_digits_fast(medium_num),
"\ttime =",
timeit("z.num_digits_fast(z.medium_num)", setup="import __main__ as z"),
"seconds",
)
print(
"> num_digits_faster()",
"\tans =",
num_digits_faster(medium_num),
"\ttime =",
timeit("z.num_digits_faster(z.medium_num)", setup="import __main__ as z"),
"seconds",
)
print("\nFor large_num = ", large_num, ":")
print(
"> num_digits()",
"\t\tans =",
num_digits(large_num),
"\ttime =",
timeit("z.num_digits(z.large_num)", setup="import __main__ as z"),
"seconds",
)
print(
"> num_digits_fast()",
"\tans =",
num_digits_fast(large_num),
"\ttime =",
timeit("z.num_digits_fast(z.large_num)", setup="import __main__ as z"),
"seconds",
)
print(
"> num_digits_faster()",
"\tans =",
num_digits_faster(large_num),
"\ttime =",
timeit("z.num_digits_faster(z.large_num)", setup="import __main__ as z"),
"seconds",
)
if __name__ == "__main__":
small_num = 262144
medium_num = 1125899906842624
large_num = 1267650600228229401496703205376
benchmark()
import doctest
doctest.testmod()
| import math
from timeit import timeit
def num_digits(n: int) -> int:
"""
Find the number of digits in a number.
>>> num_digits(12345)
5
>>> num_digits(123)
3
>>> num_digits(0)
1
>>> num_digits(-1)
1
>>> num_digits(-123456)
6
"""
digits = 0
n = abs(n)
while True:
n = n // 10
digits += 1
if n == 0:
break
return digits
def num_digits_fast(n: int) -> int:
"""
Find the number of digits in a number.
abs() is used as logarithm for negative numbers is not defined.
>>> num_digits_fast(12345)
5
>>> num_digits_fast(123)
3
>>> num_digits_fast(0)
1
>>> num_digits_fast(-1)
1
>>> num_digits_fast(-123456)
6
"""
return 1 if n == 0 else math.floor(math.log(abs(n), 10) + 1)
def num_digits_faster(n: int) -> int:
"""
Find the number of digits in a number.
abs() is used for negative numbers
>>> num_digits_faster(12345)
5
>>> num_digits_faster(123)
3
>>> num_digits_faster(0)
1
>>> num_digits_faster(-1)
1
>>> num_digits_faster(-123456)
6
"""
return len(str(abs(n)))
def benchmark() -> None:
"""
Benchmark code for comparing 3 functions,
with 3 different length int values.
"""
print("\nFor small_num = ", small_num, ":")
print(
"> num_digits()",
"\t\tans =",
num_digits(small_num),
"\ttime =",
timeit("z.num_digits(z.small_num)", setup="import __main__ as z"),
"seconds",
)
print(
"> num_digits_fast()",
"\tans =",
num_digits_fast(small_num),
"\ttime =",
timeit("z.num_digits_fast(z.small_num)", setup="import __main__ as z"),
"seconds",
)
print(
"> num_digits_faster()",
"\tans =",
num_digits_faster(small_num),
"\ttime =",
timeit("z.num_digits_faster(z.small_num)", setup="import __main__ as z"),
"seconds",
)
print("\nFor medium_num = ", medium_num, ":")
print(
"> num_digits()",
"\t\tans =",
num_digits(medium_num),
"\ttime =",
timeit("z.num_digits(z.medium_num)", setup="import __main__ as z"),
"seconds",
)
print(
"> num_digits_fast()",
"\tans =",
num_digits_fast(medium_num),
"\ttime =",
timeit("z.num_digits_fast(z.medium_num)", setup="import __main__ as z"),
"seconds",
)
print(
"> num_digits_faster()",
"\tans =",
num_digits_faster(medium_num),
"\ttime =",
timeit("z.num_digits_faster(z.medium_num)", setup="import __main__ as z"),
"seconds",
)
print("\nFor large_num = ", large_num, ":")
print(
"> num_digits()",
"\t\tans =",
num_digits(large_num),
"\ttime =",
timeit("z.num_digits(z.large_num)", setup="import __main__ as z"),
"seconds",
)
print(
"> num_digits_fast()",
"\tans =",
num_digits_fast(large_num),
"\ttime =",
timeit("z.num_digits_fast(z.large_num)", setup="import __main__ as z"),
"seconds",
)
print(
"> num_digits_faster()",
"\tans =",
num_digits_faster(large_num),
"\ttime =",
timeit("z.num_digits_faster(z.large_num)", setup="import __main__ as z"),
"seconds",
)
if __name__ == "__main__":
small_num = 262144
medium_num = 1125899906842624
large_num = 1267650600228229401496703205376
benchmark()
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
https://en.wikipedia.org/wiki/Lucas_number
"""
def recursive_lucas_number(n_th_number: int) -> int:
"""
Returns the nth lucas number
>>> recursive_lucas_number(1)
1
>>> recursive_lucas_number(20)
15127
>>> recursive_lucas_number(0)
2
>>> recursive_lucas_number(25)
167761
>>> recursive_lucas_number(-1.5)
Traceback (most recent call last):
...
TypeError: recursive_lucas_number accepts only integer arguments.
"""
if not isinstance(n_th_number, int):
raise TypeError("recursive_lucas_number accepts only integer arguments.")
if n_th_number == 0:
return 2
if n_th_number == 1:
return 1
return recursive_lucas_number(n_th_number - 1) + recursive_lucas_number(
n_th_number - 2
)
def dynamic_lucas_number(n_th_number: int) -> int:
"""
Returns the nth lucas number
>>> dynamic_lucas_number(1)
1
>>> dynamic_lucas_number(20)
15127
>>> dynamic_lucas_number(0)
2
>>> dynamic_lucas_number(25)
167761
>>> dynamic_lucas_number(-1.5)
Traceback (most recent call last):
...
TypeError: dynamic_lucas_number accepts only integer arguments.
"""
if not isinstance(n_th_number, int):
raise TypeError("dynamic_lucas_number accepts only integer arguments.")
a, b = 2, 1
for i in range(n_th_number):
a, b = b, a + b
return a
if __name__ == "__main__":
from doctest import testmod
testmod()
n = int(input("Enter the number of terms in lucas series:\n").strip())
print("Using recursive function to calculate lucas series:")
print(" ".join(str(recursive_lucas_number(i)) for i in range(n)))
print("\nUsing dynamic function to calculate lucas series:")
print(" ".join(str(dynamic_lucas_number(i)) for i in range(n)))
| """
https://en.wikipedia.org/wiki/Lucas_number
"""
def recursive_lucas_number(n_th_number: int) -> int:
"""
Returns the nth lucas number
>>> recursive_lucas_number(1)
1
>>> recursive_lucas_number(20)
15127
>>> recursive_lucas_number(0)
2
>>> recursive_lucas_number(25)
167761
>>> recursive_lucas_number(-1.5)
Traceback (most recent call last):
...
TypeError: recursive_lucas_number accepts only integer arguments.
"""
if not isinstance(n_th_number, int):
raise TypeError("recursive_lucas_number accepts only integer arguments.")
if n_th_number == 0:
return 2
if n_th_number == 1:
return 1
return recursive_lucas_number(n_th_number - 1) + recursive_lucas_number(
n_th_number - 2
)
def dynamic_lucas_number(n_th_number: int) -> int:
"""
Returns the nth lucas number
>>> dynamic_lucas_number(1)
1
>>> dynamic_lucas_number(20)
15127
>>> dynamic_lucas_number(0)
2
>>> dynamic_lucas_number(25)
167761
>>> dynamic_lucas_number(-1.5)
Traceback (most recent call last):
...
TypeError: dynamic_lucas_number accepts only integer arguments.
"""
if not isinstance(n_th_number, int):
raise TypeError("dynamic_lucas_number accepts only integer arguments.")
a, b = 2, 1
for i in range(n_th_number):
a, b = b, a + b
return a
if __name__ == "__main__":
from doctest import testmod
testmod()
n = int(input("Enter the number of terms in lucas series:\n").strip())
print("Using recursive function to calculate lucas series:")
print(" ".join(str(recursive_lucas_number(i)) for i in range(n)))
print("\nUsing dynamic function to calculate lucas series:")
print(" ".join(str(dynamic_lucas_number(i)) for i in range(n)))
| -1 |
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| def factorial(n: int) -> int:
"""
Calculate the factorial of a positive integer
https://en.wikipedia.org/wiki/Factorial
>>> import math
>>> all(factorial(i) == math.factorial(i) for i in range(20))
True
>>> factorial(0.1)
Traceback (most recent call last):
...
ValueError: factorial() only accepts integral values
>>> factorial(-1)
Traceback (most recent call last):
...
ValueError: factorial() not defined for negative values
"""
if not isinstance(n, int):
raise ValueError("factorial() only accepts integral values")
if n < 0:
raise ValueError("factorial() not defined for negative values")
return 1 if n == 0 or n == 1 else n * factorial(n - 1)
if __name__ == "__main__":
import doctest
doctest.testmod()
| def factorial(n: int) -> int:
"""
Calculate the factorial of a positive integer
https://en.wikipedia.org/wiki/Factorial
>>> import math
>>> all(factorial(i) == math.factorial(i) for i in range(20))
True
>>> factorial(0.1)
Traceback (most recent call last):
...
ValueError: factorial() only accepts integral values
>>> factorial(-1)
Traceback (most recent call last):
...
ValueError: factorial() not defined for negative values
"""
if not isinstance(n, int):
raise ValueError("factorial() only accepts integral values")
if n < 0:
raise ValueError("factorial() not defined for negative values")
return 1 if n == 0 or n == 1 else n * factorial(n - 1)
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| #!/usr/bin/env python3
"""
Created by sarathkaul on 14/11/19
Updated by lawric1 on 24/11/20
Authentication will be made via access token.
To generate your personal access token visit https://github.com/settings/tokens.
NOTE:
Never hardcode any credential information in the code. Always use an environment
file to store the private information and use the `os` module to get the information
during runtime.
Create a ".env" file in the root directory and write these two lines in that file
with your token::
#!/usr/bin/env bash
export USER_TOKEN=""
"""
import os
from typing import Any, Dict
import requests
BASE_URL = "https://api.github.com"
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
AUTHENTICATED_USER_ENDPOINT = BASE_URL + "/user"
# https://github.com/settings/tokens
USER_TOKEN = os.environ.get("USER_TOKEN", "")
def fetch_github_info(auth_token: str) -> Dict[Any, Any]:
"""
Fetch GitHub info of a user using the requests module
"""
headers = {
"Authorization": f"token {auth_token}",
"Accept": "application/vnd.github.v3+json",
}
return requests.get(AUTHENTICATED_USER_ENDPOINT, headers=headers).json()
if __name__ == "__main__": # pragma: no cover
if USER_TOKEN:
for key, value in fetch_github_info(USER_TOKEN).items():
print(f"{key}: {value}")
else:
raise ValueError("'USER_TOKEN' field cannot be empty.")
| #!/usr/bin/env python3
"""
Created by sarathkaul on 14/11/19
Updated by lawric1 on 24/11/20
Authentication will be made via access token.
To generate your personal access token visit https://github.com/settings/tokens.
NOTE:
Never hardcode any credential information in the code. Always use an environment
file to store the private information and use the `os` module to get the information
during runtime.
Create a ".env" file in the root directory and write these two lines in that file
with your token::
#!/usr/bin/env bash
export USER_TOKEN=""
"""
import os
from typing import Any, Dict
import requests
BASE_URL = "https://api.github.com"
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
AUTHENTICATED_USER_ENDPOINT = BASE_URL + "/user"
# https://github.com/settings/tokens
USER_TOKEN = os.environ.get("USER_TOKEN", "")
def fetch_github_info(auth_token: str) -> Dict[Any, Any]:
"""
Fetch GitHub info of a user using the requests module
"""
headers = {
"Authorization": f"token {auth_token}",
"Accept": "application/vnd.github.v3+json",
}
return requests.get(AUTHENTICATED_USER_ENDPOINT, headers=headers).json()
if __name__ == "__main__": # pragma: no cover
if USER_TOKEN:
for key, value in fetch_github_info(USER_TOKEN).items():
print(f"{key}: {value}")
else:
raise ValueError("'USER_TOKEN' field cannot be empty.")
| -1 |
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 1: https://projecteuler.net/problem=1
Multiples of 3 and 5
If we list all the natural numbers below 10 that are multiples of 3 or 5,
we get 3, 5, 6 and 9. The sum of these multiples is 23.
Find the sum of all the multiples of 3 or 5 below 1000.
"""
def solution(n: int = 1000) -> int:
"""
Returns the sum of all the multiples of 3 or 5 below n.
A straightforward pythonic solution using list comprehension.
>>> solution(3)
0
>>> solution(4)
3
>>> solution(10)
23
>>> solution(600)
83700
"""
return sum([i for i in range(n) if i % 3 == 0 or i % 5 == 0])
if __name__ == "__main__":
print(f"{solution() = }")
| """
Project Euler Problem 1: https://projecteuler.net/problem=1
Multiples of 3 and 5
If we list all the natural numbers below 10 that are multiples of 3 or 5,
we get 3, 5, 6 and 9. The sum of these multiples is 23.
Find the sum of all the multiples of 3 or 5 below 1000.
"""
def solution(n: int = 1000) -> int:
"""
Returns the sum of all the multiples of 3 or 5 below n.
A straightforward pythonic solution using list comprehension.
>>> solution(3)
0
>>> solution(4)
3
>>> solution(10)
23
>>> solution(600)
83700
"""
return sum([i for i in range(n) if i % 3 == 0 or i % 5 == 0])
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| #!/usr/bin/env python3
from .number_theory.prime_numbers import next_prime
class HashTable:
"""
Basic Hash Table example with open addressing and linear probing
"""
def __init__(self, size_table, charge_factor=None, lim_charge=None):
self.size_table = size_table
self.values = [None] * self.size_table
self.lim_charge = 0.75 if lim_charge is None else lim_charge
self.charge_factor = 1 if charge_factor is None else charge_factor
self.__aux_list = []
self._keys = {}
def keys(self):
return self._keys
def balanced_factor(self):
return sum([1 for slot in self.values if slot is not None]) / (
self.size_table * self.charge_factor
)
def hash_function(self, key):
return key % self.size_table
def _step_by_step(self, step_ord):
print(f"step {step_ord}")
print([i for i in range(len(self.values))])
print(self.values)
def bulk_insert(self, values):
i = 1
self.__aux_list = values
for value in values:
self.insert_data(value)
self._step_by_step(i)
i += 1
def _set_value(self, key, data):
self.values[key] = data
self._keys[key] = data
def _collision_resolution(self, key, data=None):
new_key = self.hash_function(key + 1)
while self.values[new_key] is not None and self.values[new_key] != key:
if self.values.count(None) > 0:
new_key = self.hash_function(new_key + 1)
else:
new_key = None
break
return new_key
def rehashing(self):
survivor_values = [value for value in self.values if value is not None]
self.size_table = next_prime(self.size_table, factor=2)
self._keys.clear()
self.values = [None] * self.size_table # hell's pointers D: don't DRY ;/
for value in survivor_values:
self.insert_data(value)
def insert_data(self, data):
key = self.hash_function(data)
if self.values[key] is None:
self._set_value(key, data)
elif self.values[key] == data:
pass
else:
collision_resolution = self._collision_resolution(key, data)
if collision_resolution is not None:
self._set_value(collision_resolution, data)
else:
self.rehashing()
self.insert_data(data)
| #!/usr/bin/env python3
from .number_theory.prime_numbers import next_prime
class HashTable:
"""
Basic Hash Table example with open addressing and linear probing
"""
def __init__(self, size_table, charge_factor=None, lim_charge=None):
self.size_table = size_table
self.values = [None] * self.size_table
self.lim_charge = 0.75 if lim_charge is None else lim_charge
self.charge_factor = 1 if charge_factor is None else charge_factor
self.__aux_list = []
self._keys = {}
def keys(self):
return self._keys
def balanced_factor(self):
return sum([1 for slot in self.values if slot is not None]) / (
self.size_table * self.charge_factor
)
def hash_function(self, key):
return key % self.size_table
def _step_by_step(self, step_ord):
print(f"step {step_ord}")
print([i for i in range(len(self.values))])
print(self.values)
def bulk_insert(self, values):
i = 1
self.__aux_list = values
for value in values:
self.insert_data(value)
self._step_by_step(i)
i += 1
def _set_value(self, key, data):
self.values[key] = data
self._keys[key] = data
def _collision_resolution(self, key, data=None):
new_key = self.hash_function(key + 1)
while self.values[new_key] is not None and self.values[new_key] != key:
if self.values.count(None) > 0:
new_key = self.hash_function(new_key + 1)
else:
new_key = None
break
return new_key
def rehashing(self):
survivor_values = [value for value in self.values if value is not None]
self.size_table = next_prime(self.size_table, factor=2)
self._keys.clear()
self.values = [None] * self.size_table # hell's pointers D: don't DRY ;/
for value in survivor_values:
self.insert_data(value)
def insert_data(self, data):
key = self.hash_function(data)
if self.values[key] is None:
self._set_value(key, data)
elif self.values[key] == data:
pass
else:
collision_resolution = self._collision_resolution(key, data)
if collision_resolution is not None:
self._set_value(collision_resolution, data)
else:
self.rehashing()
self.insert_data(data)
| -1 |
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """Uses Pythagoras theorem to calculate the distance between two points in space."""
import math
class Point:
def __init__(self, x, y, z):
self.x = x
self.y = y
self.z = z
def __repr__(self) -> str:
return f"Point({self.x}, {self.y}, {self.z})"
def distance(a: Point, b: Point) -> float:
return math.sqrt(abs((b.x - a.x) ** 2 + (b.y - a.y) ** 2 + (b.z - a.z) ** 2))
def test_distance() -> None:
"""
>>> point1 = Point(2, -1, 7)
>>> point2 = Point(1, -3, 5)
>>> print(f"Distance from {point1} to {point2} is {distance(point1, point2)}")
Distance from Point(2, -1, 7) to Point(1, -3, 5) is 3.0
"""
pass
if __name__ == "__main__":
import doctest
doctest.testmod()
| """Uses Pythagoras theorem to calculate the distance between two points in space."""
import math
class Point:
def __init__(self, x, y, z):
self.x = x
self.y = y
self.z = z
def __repr__(self) -> str:
return f"Point({self.x}, {self.y}, {self.z})"
def distance(a: Point, b: Point) -> float:
return math.sqrt(abs((b.x - a.x) ** 2 + (b.y - a.y) ** 2 + (b.z - a.z) ** 2))
def test_distance() -> None:
"""
>>> point1 = Point(2, -1, 7)
>>> point2 = Point(1, -3, 5)
>>> print(f"Distance from {point1} to {point2} is {distance(point1, point2)}")
Distance from Point(2, -1, 7) to Point(1, -3, 5) is 3.0
"""
pass
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| def mixed_keyword(key: str = "college", pt: str = "UNIVERSITY") -> str:
"""
For key:hello
H E L O
A B C D
F G I J
K M N P
Q R S T
U V W X
Y Z
and map vertically
>>> mixed_keyword("college", "UNIVERSITY") # doctest: +NORMALIZE_WHITESPACE
{'A': 'C', 'B': 'A', 'C': 'I', 'D': 'P', 'E': 'U', 'F': 'Z', 'G': 'O', 'H': 'B',
'I': 'J', 'J': 'Q', 'K': 'V', 'L': 'L', 'M': 'D', 'N': 'K', 'O': 'R', 'P': 'W',
'Q': 'E', 'R': 'F', 'S': 'M', 'T': 'S', 'U': 'X', 'V': 'G', 'W': 'H', 'X': 'N',
'Y': 'T', 'Z': 'Y'}
'XKJGUFMJST'
"""
key = key.upper()
pt = pt.upper()
temp = []
for i in key:
if i not in temp:
temp.append(i)
len_temp = len(temp)
# print(temp)
alpha = []
modalpha = []
for i in range(65, 91):
t = chr(i)
alpha.append(t)
if t not in temp:
temp.append(t)
# print(temp)
r = int(26 / 4)
# print(r)
k = 0
for i in range(r):
t = []
for j in range(len_temp):
t.append(temp[k])
if not (k < 25):
break
k += 1
modalpha.append(t)
# print(modalpha)
d = {}
j = 0
k = 0
for j in range(len_temp):
for i in modalpha:
if not (len(i) - 1 >= j):
break
d[alpha[k]] = i[j]
if not k < 25:
break
k += 1
print(d)
cypher = ""
for i in pt:
cypher += d[i]
return cypher
print(mixed_keyword("college", "UNIVERSITY"))
| def mixed_keyword(key: str = "college", pt: str = "UNIVERSITY") -> str:
"""
For key:hello
H E L O
A B C D
F G I J
K M N P
Q R S T
U V W X
Y Z
and map vertically
>>> mixed_keyword("college", "UNIVERSITY") # doctest: +NORMALIZE_WHITESPACE
{'A': 'C', 'B': 'A', 'C': 'I', 'D': 'P', 'E': 'U', 'F': 'Z', 'G': 'O', 'H': 'B',
'I': 'J', 'J': 'Q', 'K': 'V', 'L': 'L', 'M': 'D', 'N': 'K', 'O': 'R', 'P': 'W',
'Q': 'E', 'R': 'F', 'S': 'M', 'T': 'S', 'U': 'X', 'V': 'G', 'W': 'H', 'X': 'N',
'Y': 'T', 'Z': 'Y'}
'XKJGUFMJST'
"""
key = key.upper()
pt = pt.upper()
temp = []
for i in key:
if i not in temp:
temp.append(i)
len_temp = len(temp)
# print(temp)
alpha = []
modalpha = []
for i in range(65, 91):
t = chr(i)
alpha.append(t)
if t not in temp:
temp.append(t)
# print(temp)
r = int(26 / 4)
# print(r)
k = 0
for i in range(r):
t = []
for j in range(len_temp):
t.append(temp[k])
if not (k < 25):
break
k += 1
modalpha.append(t)
# print(modalpha)
d = {}
j = 0
k = 0
for j in range(len_temp):
for i in modalpha:
if not (len(i) - 1 >= j):
break
d[alpha[k]] = i[j]
if not k < 25:
break
k += 1
print(d)
cypher = ""
for i in pt:
cypher += d[i]
return cypher
print(mixed_keyword("college", "UNIVERSITY"))
| -1 |
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| #!/usr/bin/env python3
import importlib.util
import json
import os
import pathlib
from types import ModuleType
from typing import Dict, List
import pytest
import requests
PROJECT_EULER_DIR_PATH = pathlib.Path.cwd().joinpath("project_euler")
PROJECT_EULER_ANSWERS_PATH = pathlib.Path.cwd().joinpath(
"scripts", "project_euler_answers.json"
)
with open(PROJECT_EULER_ANSWERS_PATH) as file_handle:
PROBLEM_ANSWERS: Dict[str, str] = json.load(file_handle)
def convert_path_to_module(file_path: pathlib.Path) -> ModuleType:
"""Converts a file path to a Python module"""
spec = importlib.util.spec_from_file_location(file_path.name, str(file_path))
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
return module
def all_solution_file_paths() -> List[pathlib.Path]:
"""Collects all the solution file path in the Project Euler directory"""
solution_file_paths = []
for problem_dir_path in PROJECT_EULER_DIR_PATH.iterdir():
if problem_dir_path.is_file() or problem_dir_path.name.startswith("_"):
continue
for file_path in problem_dir_path.iterdir():
if file_path.suffix != ".py" or file_path.name.startswith(("_", "test")):
continue
solution_file_paths.append(file_path)
return solution_file_paths
def get_files_url() -> str:
"""Return the pull request number which triggered this action."""
with open(os.environ["GITHUB_EVENT_PATH"]) as file:
event = json.load(file)
return event["pull_request"]["url"] + "/files"
def added_solution_file_path() -> List[pathlib.Path]:
"""Collects only the solution file path which got added in the current
pull request.
This will only be triggered if the script is ran from GitHub Actions.
"""
solution_file_paths = []
headers = {
"Accept": "application/vnd.github.v3+json",
"Authorization": "token " + os.environ["GITHUB_TOKEN"],
}
files = requests.get(get_files_url(), headers=headers).json()
for file in files:
filepath = pathlib.Path.cwd().joinpath(file["filename"])
if (
filepath.suffix != ".py"
or filepath.name.startswith(("_", "test"))
or not filepath.name.startswith("sol")
):
continue
solution_file_paths.append(filepath)
return solution_file_paths
def collect_solution_file_paths() -> List[pathlib.Path]:
if os.environ.get("CI") and os.environ.get("GITHUB_EVENT_NAME") == "pull_request":
# Return only if there are any, otherwise default to all solutions
if filepaths := added_solution_file_path():
return filepaths
return all_solution_file_paths()
@pytest.mark.parametrize(
"solution_path",
collect_solution_file_paths(),
ids=lambda path: f"{path.parent.name}/{path.name}",
)
def test_project_euler(solution_path: pathlib.Path) -> None:
"""Testing for all Project Euler solutions"""
# problem_[extract this part] and pad it with zeroes for width 3
problem_number: str = solution_path.parent.name[8:].zfill(3)
expected: str = PROBLEM_ANSWERS[problem_number]
solution_module = convert_path_to_module(solution_path)
answer = str(solution_module.solution())
assert answer == expected, f"Expected {expected} but got {answer}"
| #!/usr/bin/env python3
import importlib.util
import json
import os
import pathlib
from types import ModuleType
from typing import Dict, List
import pytest
import requests
PROJECT_EULER_DIR_PATH = pathlib.Path.cwd().joinpath("project_euler")
PROJECT_EULER_ANSWERS_PATH = pathlib.Path.cwd().joinpath(
"scripts", "project_euler_answers.json"
)
with open(PROJECT_EULER_ANSWERS_PATH) as file_handle:
PROBLEM_ANSWERS: Dict[str, str] = json.load(file_handle)
def convert_path_to_module(file_path: pathlib.Path) -> ModuleType:
"""Converts a file path to a Python module"""
spec = importlib.util.spec_from_file_location(file_path.name, str(file_path))
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
return module
def all_solution_file_paths() -> List[pathlib.Path]:
"""Collects all the solution file path in the Project Euler directory"""
solution_file_paths = []
for problem_dir_path in PROJECT_EULER_DIR_PATH.iterdir():
if problem_dir_path.is_file() or problem_dir_path.name.startswith("_"):
continue
for file_path in problem_dir_path.iterdir():
if file_path.suffix != ".py" or file_path.name.startswith(("_", "test")):
continue
solution_file_paths.append(file_path)
return solution_file_paths
def get_files_url() -> str:
"""Return the pull request number which triggered this action."""
with open(os.environ["GITHUB_EVENT_PATH"]) as file:
event = json.load(file)
return event["pull_request"]["url"] + "/files"
def added_solution_file_path() -> List[pathlib.Path]:
"""Collects only the solution file path which got added in the current
pull request.
This will only be triggered if the script is ran from GitHub Actions.
"""
solution_file_paths = []
headers = {
"Accept": "application/vnd.github.v3+json",
"Authorization": "token " + os.environ["GITHUB_TOKEN"],
}
files = requests.get(get_files_url(), headers=headers).json()
for file in files:
filepath = pathlib.Path.cwd().joinpath(file["filename"])
if (
filepath.suffix != ".py"
or filepath.name.startswith(("_", "test"))
or not filepath.name.startswith("sol")
):
continue
solution_file_paths.append(filepath)
return solution_file_paths
def collect_solution_file_paths() -> List[pathlib.Path]:
if os.environ.get("CI") and os.environ.get("GITHUB_EVENT_NAME") == "pull_request":
# Return only if there are any, otherwise default to all solutions
if filepaths := added_solution_file_path():
return filepaths
return all_solution_file_paths()
@pytest.mark.parametrize(
"solution_path",
collect_solution_file_paths(),
ids=lambda path: f"{path.parent.name}/{path.name}",
)
def test_project_euler(solution_path: pathlib.Path) -> None:
"""Testing for all Project Euler solutions"""
# problem_[extract this part] and pad it with zeroes for width 3
problem_number: str = solution_path.parent.name[8:].zfill(3)
expected: str = PROBLEM_ANSWERS[problem_number]
solution_module = convert_path_to_module(solution_path)
answer = str(solution_module.solution())
assert answer == expected, f"Expected {expected} but got {answer}"
| -1 |
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
* Binary Exponentiation with Multiplication
* This is a method to find a*b in a time complexity of O(log b)
* This is one of the most commonly used methods of finding result of multiplication.
* Also useful in cases where solution to (a*b)%c is required,
* where a,b,c can be numbers over the computers calculation limits.
* Done using iteration, can also be done using recursion
* @author chinmoy159
* @version 1.0 dated 10/08/2017
"""
def b_expo(a, b):
res = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def b_expo_mod(a, b, c):
res = 0
while b > 0:
if b & 1:
res = ((res % c) + (a % c)) % c
a += a
b >>= 1
return res
"""
* Wondering how this method works !
* It's pretty simple.
* Let's say you need to calculate a ^ b
* RULE 1 : a * b = (a+a) * (b/2) ---- example : 4 * 4 = (4+4) * (4/2) = 8 * 2
* RULE 2 : IF b is ODD, then ---- a * b = a + (a * (b - 1)) :: where (b - 1) is even.
* Once b is even, repeat the process to get a * b
* Repeat the process till b = 1 OR b = 0, because a*1 = a AND a*0 = 0
*
* As far as the modulo is concerned,
* the fact : (a+b) % c = ((a%c) + (b%c)) % c
* Now apply RULE 1 OR 2, whichever is required.
"""
| """
* Binary Exponentiation with Multiplication
* This is a method to find a*b in a time complexity of O(log b)
* This is one of the most commonly used methods of finding result of multiplication.
* Also useful in cases where solution to (a*b)%c is required,
* where a,b,c can be numbers over the computers calculation limits.
* Done using iteration, can also be done using recursion
* @author chinmoy159
* @version 1.0 dated 10/08/2017
"""
def b_expo(a, b):
res = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def b_expo_mod(a, b, c):
res = 0
while b > 0:
if b & 1:
res = ((res % c) + (a % c)) % c
a += a
b >>= 1
return res
"""
* Wondering how this method works !
* It's pretty simple.
* Let's say you need to calculate a ^ b
* RULE 1 : a * b = (a+a) * (b/2) ---- example : 4 * 4 = (4+4) * (4/2) = 8 * 2
* RULE 2 : IF b is ODD, then ---- a * b = a + (a * (b - 1)) :: where (b - 1) is even.
* Once b is even, repeat the process to get a * b
* Repeat the process till b = 1 OR b = 0, because a*1 = a AND a*0 = 0
*
* As far as the modulo is concerned,
* the fact : (a+b) % c = ((a%c) + (b%c)) % c
* Now apply RULE 1 OR 2, whichever is required.
"""
| -1 |
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
https://en.wikipedia.org/wiki/Doubly_linked_list
"""
class Node:
def __init__(self, data):
self.data = data
self.previous = None
self.next = None
def __str__(self):
return f"{self.data}"
class DoublyLinkedList:
def __init__(self):
self.head = None
self.tail = None
def __iter__(self):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.insert_at_head('b')
>>> linked_list.insert_at_head('a')
>>> linked_list.insert_at_tail('c')
>>> tuple(linked_list)
('a', 'b', 'c')
"""
node = self.head
while node:
yield node.data
node = node.next
def __str__(self):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.insert_at_tail('a')
>>> linked_list.insert_at_tail('b')
>>> linked_list.insert_at_tail('c')
>>> str(linked_list)
'a->b->c'
"""
return "->".join([str(item) for item in self])
def __len__(self):
"""
>>> linked_list = DoublyLinkedList()
>>> for i in range(0, 5):
... linked_list.insert_at_nth(i, i + 1)
>>> len(linked_list) == 5
True
"""
return len(tuple(iter(self)))
def insert_at_head(self, data):
self.insert_at_nth(0, data)
def insert_at_tail(self, data):
self.insert_at_nth(len(self), data)
def insert_at_nth(self, index: int, data):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.insert_at_nth(-1, 666)
Traceback (most recent call last):
....
IndexError: list index out of range
>>> linked_list.insert_at_nth(1, 666)
Traceback (most recent call last):
....
IndexError: list index out of range
>>> linked_list.insert_at_nth(0, 2)
>>> linked_list.insert_at_nth(0, 1)
>>> linked_list.insert_at_nth(2, 4)
>>> linked_list.insert_at_nth(2, 3)
>>> str(linked_list)
'1->2->3->4'
>>> linked_list.insert_at_nth(5, 5)
Traceback (most recent call last):
....
IndexError: list index out of range
"""
if not 0 <= index <= len(self):
raise IndexError("list index out of range")
new_node = Node(data)
if self.head is None:
self.head = self.tail = new_node
elif index == 0:
self.head.previous = new_node
new_node.next = self.head
self.head = new_node
elif index == len(self):
self.tail.next = new_node
new_node.previous = self.tail
self.tail = new_node
else:
temp = self.head
for i in range(0, index):
temp = temp.next
temp.previous.next = new_node
new_node.previous = temp.previous
new_node.next = temp
temp.previous = new_node
def delete_head(self):
return self.delete_at_nth(0)
def delete_tail(self):
return self.delete_at_nth(len(self) - 1)
def delete_at_nth(self, index: int):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.delete_at_nth(0)
Traceback (most recent call last):
....
IndexError: list index out of range
>>> for i in range(0, 5):
... linked_list.insert_at_nth(i, i + 1)
>>> linked_list.delete_at_nth(0) == 1
True
>>> linked_list.delete_at_nth(3) == 5
True
>>> linked_list.delete_at_nth(1) == 3
True
>>> str(linked_list)
'2->4'
>>> linked_list.delete_at_nth(2)
Traceback (most recent call last):
....
IndexError: list index out of range
"""
if not 0 <= index <= len(self) - 1:
raise IndexError("list index out of range")
delete_node = self.head # default first node
if len(self) == 1:
self.head = self.tail = None
elif index == 0:
self.head = self.head.next
self.head.previous = None
elif index == len(self) - 1:
delete_node = self.tail
self.tail = self.tail.previous
self.tail.next = None
else:
temp = self.head
for i in range(0, index):
temp = temp.next
delete_node = temp
temp.next.previous = temp.previous
temp.previous.next = temp.next
return delete_node.data
def delete(self, data) -> str:
current = self.head
while current.data != data: # Find the position to delete
if current.next:
current = current.next
else: # We have reached the end an no value matches
return "No data matching given value"
if current == self.head:
self.delete_head()
elif current == self.tail:
self.delete_tail()
else: # Before: 1 <--> 2(current) <--> 3
current.previous.next = current.next # 1 --> 3
current.next.previous = current.previous # 1 <--> 3
return data
def is_empty(self):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.is_empty()
True
>>> linked_list.insert_at_tail(1)
>>> linked_list.is_empty()
False
"""
return len(self) == 0
def test_doubly_linked_list() -> None:
"""
>>> test_doubly_linked_list()
"""
linked_list = DoublyLinkedList()
assert linked_list.is_empty() is True
assert str(linked_list) == ""
try:
linked_list.delete_head()
assert False # This should not happen.
except IndexError:
assert True # This should happen.
try:
linked_list.delete_tail()
assert False # This should not happen.
except IndexError:
assert True # This should happen.
for i in range(10):
assert len(linked_list) == i
linked_list.insert_at_nth(i, i + 1)
assert str(linked_list) == "->".join(str(i) for i in range(1, 11))
linked_list.insert_at_head(0)
linked_list.insert_at_tail(11)
assert str(linked_list) == "->".join(str(i) for i in range(0, 12))
assert linked_list.delete_head() == 0
assert linked_list.delete_at_nth(9) == 10
assert linked_list.delete_tail() == 11
assert len(linked_list) == 9
assert str(linked_list) == "->".join(str(i) for i in range(1, 10))
if __name__ == "__main__":
from doctest import testmod
testmod()
| """
https://en.wikipedia.org/wiki/Doubly_linked_list
"""
class Node:
def __init__(self, data):
self.data = data
self.previous = None
self.next = None
def __str__(self):
return f"{self.data}"
class DoublyLinkedList:
def __init__(self):
self.head = None
self.tail = None
def __iter__(self):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.insert_at_head('b')
>>> linked_list.insert_at_head('a')
>>> linked_list.insert_at_tail('c')
>>> tuple(linked_list)
('a', 'b', 'c')
"""
node = self.head
while node:
yield node.data
node = node.next
def __str__(self):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.insert_at_tail('a')
>>> linked_list.insert_at_tail('b')
>>> linked_list.insert_at_tail('c')
>>> str(linked_list)
'a->b->c'
"""
return "->".join([str(item) for item in self])
def __len__(self):
"""
>>> linked_list = DoublyLinkedList()
>>> for i in range(0, 5):
... linked_list.insert_at_nth(i, i + 1)
>>> len(linked_list) == 5
True
"""
return len(tuple(iter(self)))
def insert_at_head(self, data):
self.insert_at_nth(0, data)
def insert_at_tail(self, data):
self.insert_at_nth(len(self), data)
def insert_at_nth(self, index: int, data):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.insert_at_nth(-1, 666)
Traceback (most recent call last):
....
IndexError: list index out of range
>>> linked_list.insert_at_nth(1, 666)
Traceback (most recent call last):
....
IndexError: list index out of range
>>> linked_list.insert_at_nth(0, 2)
>>> linked_list.insert_at_nth(0, 1)
>>> linked_list.insert_at_nth(2, 4)
>>> linked_list.insert_at_nth(2, 3)
>>> str(linked_list)
'1->2->3->4'
>>> linked_list.insert_at_nth(5, 5)
Traceback (most recent call last):
....
IndexError: list index out of range
"""
if not 0 <= index <= len(self):
raise IndexError("list index out of range")
new_node = Node(data)
if self.head is None:
self.head = self.tail = new_node
elif index == 0:
self.head.previous = new_node
new_node.next = self.head
self.head = new_node
elif index == len(self):
self.tail.next = new_node
new_node.previous = self.tail
self.tail = new_node
else:
temp = self.head
for i in range(0, index):
temp = temp.next
temp.previous.next = new_node
new_node.previous = temp.previous
new_node.next = temp
temp.previous = new_node
def delete_head(self):
return self.delete_at_nth(0)
def delete_tail(self):
return self.delete_at_nth(len(self) - 1)
def delete_at_nth(self, index: int):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.delete_at_nth(0)
Traceback (most recent call last):
....
IndexError: list index out of range
>>> for i in range(0, 5):
... linked_list.insert_at_nth(i, i + 1)
>>> linked_list.delete_at_nth(0) == 1
True
>>> linked_list.delete_at_nth(3) == 5
True
>>> linked_list.delete_at_nth(1) == 3
True
>>> str(linked_list)
'2->4'
>>> linked_list.delete_at_nth(2)
Traceback (most recent call last):
....
IndexError: list index out of range
"""
if not 0 <= index <= len(self) - 1:
raise IndexError("list index out of range")
delete_node = self.head # default first node
if len(self) == 1:
self.head = self.tail = None
elif index == 0:
self.head = self.head.next
self.head.previous = None
elif index == len(self) - 1:
delete_node = self.tail
self.tail = self.tail.previous
self.tail.next = None
else:
temp = self.head
for i in range(0, index):
temp = temp.next
delete_node = temp
temp.next.previous = temp.previous
temp.previous.next = temp.next
return delete_node.data
def delete(self, data) -> str:
current = self.head
while current.data != data: # Find the position to delete
if current.next:
current = current.next
else: # We have reached the end an no value matches
return "No data matching given value"
if current == self.head:
self.delete_head()
elif current == self.tail:
self.delete_tail()
else: # Before: 1 <--> 2(current) <--> 3
current.previous.next = current.next # 1 --> 3
current.next.previous = current.previous # 1 <--> 3
return data
def is_empty(self):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.is_empty()
True
>>> linked_list.insert_at_tail(1)
>>> linked_list.is_empty()
False
"""
return len(self) == 0
def test_doubly_linked_list() -> None:
"""
>>> test_doubly_linked_list()
"""
linked_list = DoublyLinkedList()
assert linked_list.is_empty() is True
assert str(linked_list) == ""
try:
linked_list.delete_head()
assert False # This should not happen.
except IndexError:
assert True # This should happen.
try:
linked_list.delete_tail()
assert False # This should not happen.
except IndexError:
assert True # This should happen.
for i in range(10):
assert len(linked_list) == i
linked_list.insert_at_nth(i, i + 1)
assert str(linked_list) == "->".join(str(i) for i in range(1, 11))
linked_list.insert_at_head(0)
linked_list.insert_at_tail(11)
assert str(linked_list) == "->".join(str(i) for i in range(0, 12))
assert linked_list.delete_head() == 0
assert linked_list.delete_at_nth(9) == 10
assert linked_list.delete_tail() == 11
assert len(linked_list) == 9
assert str(linked_list) == "->".join(str(i) for i in range(1, 10))
if __name__ == "__main__":
from doctest import testmod
testmod()
| -1 |
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # Factorial of a number using memoization
from functools import lru_cache
@lru_cache
def factorial(num: int) -> int:
"""
>>> factorial(7)
5040
>>> factorial(-1)
Traceback (most recent call last):
...
ValueError: Number should not be negative.
>>> [factorial(i) for i in range(10)]
[1, 1, 2, 6, 24, 120, 720, 5040, 40320, 362880]
"""
if num < 0:
raise ValueError("Number should not be negative.")
return 1 if num in (0, 1) else num * factorial(num - 1)
if __name__ == "__main__":
import doctest
doctest.testmod()
| # Factorial of a number using memoization
from functools import lru_cache
@lru_cache
def factorial(num: int) -> int:
"""
>>> factorial(7)
5040
>>> factorial(-1)
Traceback (most recent call last):
...
ValueError: Number should not be negative.
>>> [factorial(i) for i in range(10)]
[1, 1, 2, 6, 24, 120, 720, 5040, 40320, 362880]
"""
if num < 0:
raise ValueError("Number should not be negative.")
return 1 if num in (0, 1) else num * factorial(num - 1)
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 4,278 | fix(mypy): Fix annotations for 13 cipher algorithms | Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| dhruvmanila | 2021-03-20T09:09:15Z | 2021-03-22T06:59:51Z | 99a42f2b5821356718fb7d011ac711a6b4a63a83 | 14bcb580d55ee90614ad258ea31ef8fe4e4b5c40 | fix(mypy): Fix annotations for 13 cipher algorithms. Issue: #4052
```console
$ git diff master --name-only
ciphers/a1z26.py
ciphers/affine_cipher.py
ciphers/atbash.py
ciphers/base32.py
ciphers/base85.py
ciphers/beaufort_cipher.py
ciphers/brute_force_caesar_cipher.py
ciphers/cryptomath_module.py
ciphers/decrypt_caesar_with_chi_squared.py
ciphers/diffie.py
ciphers/elgamal_key_generator.py
ciphers/enigma_machine2.py
ciphers/rsa_key_generator.py
```
Running `mypy`:
```console
$ git diff master --name-only | xargs -I% mypy --strict %
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
Success: no issues found in 1 source file
```
### **Describe your change:**
* [ ] Add an algorithm?
* [x] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [ ] All new Python files are placed inside an existing directory.
* [ ] All filenames are in all lowercase characters with no spaces or dashes.
* [ ] All functions and variable names follow Python naming conventions.
* [ ] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [ ] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [ ] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Output:
Enter an Infix Equation = a + b ^c
Symbol | Stack | Postfix
----------------------------
c | | c
^ | ^ | c
b | ^ | cb
+ | + | cb^
a | + | cb^a
| | cb^a+
a+b^c (Infix) -> +a^bc (Prefix)
"""
def infix_2_postfix(Infix):
Stack = []
Postfix = []
priority = {
"^": 3,
"*": 2,
"/": 2,
"%": 2,
"+": 1,
"-": 1,
} # Priority of each operator
print_width = len(Infix) if (len(Infix) > 7) else 7
# Print table header for output
print(
"Symbol".center(8),
"Stack".center(print_width),
"Postfix".center(print_width),
sep=" | ",
)
print("-" * (print_width * 3 + 7))
for x in Infix:
if x.isalpha() or x.isdigit():
Postfix.append(x) # if x is Alphabet / Digit, add it to Postfix
elif x == "(":
Stack.append(x) # if x is "(" push to Stack
elif x == ")": # if x is ")" pop stack until "(" is encountered
while Stack[-1] != "(":
Postfix.append(Stack.pop()) # Pop stack & add the content to Postfix
Stack.pop()
else:
if len(Stack) == 0:
Stack.append(x) # If stack is empty, push x to stack
else: # while priority of x is not > priority of element in the stack
while len(Stack) > 0 and priority[x] <= priority[Stack[-1]]:
Postfix.append(Stack.pop()) # pop stack & add to Postfix
Stack.append(x) # push x to stack
print(
x.center(8),
("".join(Stack)).ljust(print_width),
("".join(Postfix)).ljust(print_width),
sep=" | ",
) # Output in tabular format
while len(Stack) > 0: # while stack is not empty
Postfix.append(Stack.pop()) # pop stack & add to Postfix
print(
" ".center(8),
("".join(Stack)).ljust(print_width),
("".join(Postfix)).ljust(print_width),
sep=" | ",
) # Output in tabular format
return "".join(Postfix) # return Postfix as str
def infix_2_prefix(Infix):
Infix = list(Infix[::-1]) # reverse the infix equation
for i in range(len(Infix)):
if Infix[i] == "(":
Infix[i] = ")" # change "(" to ")"
elif Infix[i] == ")":
Infix[i] = "(" # change ")" to "("
return (infix_2_postfix("".join(Infix)))[
::-1
] # call infix_2_postfix on Infix, return reverse of Postfix
if __name__ == "__main__":
Infix = input("\nEnter an Infix Equation = ") # Input an Infix equation
Infix = "".join(Infix.split()) # Remove spaces from the input
print("\n\t", Infix, "(Infix) -> ", infix_2_prefix(Infix), "(Prefix)")
| """
Output:
Enter an Infix Equation = a + b ^c
Symbol | Stack | Postfix
----------------------------
c | | c
^ | ^ | c
b | ^ | cb
+ | + | cb^
a | + | cb^a
| | cb^a+
a+b^c (Infix) -> +a^bc (Prefix)
"""
def infix_2_postfix(Infix):
Stack = []
Postfix = []
priority = {
"^": 3,
"*": 2,
"/": 2,
"%": 2,
"+": 1,
"-": 1,
} # Priority of each operator
print_width = len(Infix) if (len(Infix) > 7) else 7
# Print table header for output
print(
"Symbol".center(8),
"Stack".center(print_width),
"Postfix".center(print_width),
sep=" | ",
)
print("-" * (print_width * 3 + 7))
for x in Infix:
if x.isalpha() or x.isdigit():
Postfix.append(x) # if x is Alphabet / Digit, add it to Postfix
elif x == "(":
Stack.append(x) # if x is "(" push to Stack
elif x == ")": # if x is ")" pop stack until "(" is encountered
while Stack[-1] != "(":
Postfix.append(Stack.pop()) # Pop stack & add the content to Postfix
Stack.pop()
else:
if len(Stack) == 0:
Stack.append(x) # If stack is empty, push x to stack
else: # while priority of x is not > priority of element in the stack
while len(Stack) > 0 and priority[x] <= priority[Stack[-1]]:
Postfix.append(Stack.pop()) # pop stack & add to Postfix
Stack.append(x) # push x to stack
print(
x.center(8),
("".join(Stack)).ljust(print_width),
("".join(Postfix)).ljust(print_width),
sep=" | ",
) # Output in tabular format
while len(Stack) > 0: # while stack is not empty
Postfix.append(Stack.pop()) # pop stack & add to Postfix
print(
" ".center(8),
("".join(Stack)).ljust(print_width),
("".join(Postfix)).ljust(print_width),
sep=" | ",
) # Output in tabular format
return "".join(Postfix) # return Postfix as str
def infix_2_prefix(Infix):
Infix = list(Infix[::-1]) # reverse the infix equation
for i in range(len(Infix)):
if Infix[i] == "(":
Infix[i] = ")" # change "(" to ")"
elif Infix[i] == ")":
Infix[i] = "(" # change ")" to "("
return (infix_2_postfix("".join(Infix)))[
::-1
] # call infix_2_postfix on Infix, return reverse of Postfix
if __name__ == "__main__":
Infix = input("\nEnter an Infix Equation = ") # Input an Infix equation
Infix = "".join(Infix.split()) # Remove spaces from the input
print("\n\t", Infix, "(Infix) -> ", infix_2_prefix(Infix), "(Prefix)")
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v3.2.0
hooks:
- id: check-executables-have-shebangs
- id: check-yaml
- id: end-of-file-fixer
types: [python]
- id: trailing-whitespace
exclude: |
(?x)^(
data_structures/heap/binomial_heap.py
)$
- id: requirements-txt-fixer
- repo: https://github.com/psf/black
rev: stable
hooks:
- id: black
- repo: https://github.com/PyCQA/isort
rev: 5.5.3
hooks:
- id: isort
args:
- --profile=black
- repo: https://gitlab.com/pycqa/flake8
rev: 3.8.3
hooks:
- id: flake8
args:
- --ignore=E203,W503
- --max-complexity=25
- --max-line-length=88
# FIXME: fix mypy errors and then uncomment this
# - repo: https://github.com/pre-commit/mirrors-mypy
# rev: v0.782
# hooks:
# - id: mypy
# args:
# - --ignore-missing-imports
- repo: https://github.com/codespell-project/codespell
rev: v1.17.1
hooks:
- id: codespell
args:
- --ignore-words-list=ans,fo,followings,hist,iff,mater,secant,som,tim
- --skip="./.*,./other/dictionary.txt,./other/words,./project_euler/problem_022/p022_names.txt"
- --quiet-level=2
exclude: |
(?x)^(
other/dictionary.txt |
other/words |
project_euler/problem_022/p022_names.txt
)$
- repo: local
hooks:
- id: validate-filenames
name: Validate filenames
entry: ./scripts/validate_filenames.py
language: script
pass_filenames: false
| repos:
- repo: https://github.com/pre-commit/pre-commit-hooks
rev: v3.4.0
hooks:
- id: check-executables-have-shebangs
- id: check-yaml
- id: end-of-file-fixer
types: [python]
- id: trailing-whitespace
exclude: |
(?x)^(
data_structures/heap/binomial_heap.py
)$
- id: requirements-txt-fixer
- repo: https://github.com/psf/black
rev: 20.8b1
hooks:
- id: black
- repo: https://github.com/PyCQA/isort
rev: 5.7.0
hooks:
- id: isort
args:
- --profile=black
- repo: https://gitlab.com/pycqa/flake8
rev: 3.9.0
hooks:
- id: flake8
args:
- --ignore=E203,W503
- --max-complexity=25
- --max-line-length=88
# FIXME: fix mypy errors and then uncomment this
# - repo: https://github.com/pre-commit/mirrors-mypy
# rev: v0.782
# hooks:
# - id: mypy
# args:
# - --ignore-missing-imports
- repo: https://github.com/codespell-project/codespell
rev: v2.0.0
hooks:
- id: codespell
args:
- --ignore-words-list=ans,crate,fo,followings,hist,iff,mater,secant,som,tim
- --skip="./.*,./other/dictionary.txt,./other/words,./project_euler/problem_022/p022_names.txt"
- --quiet-level=2
exclude: |
(?x)^(
other/dictionary.txt |
other/words |
project_euler/problem_022/p022_names.txt
)$
- repo: local
hooks:
- id: validate-filenames
name: Validate filenames
entry: ./scripts/validate_filenames.py
language: script
pass_filenames: false
| 1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
|
## Arithmetic Analysis
* [Bisection](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/bisection.py)
* [Gaussian Elimination](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/gaussian_elimination.py)
* [In Static Equilibrium](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/in_static_equilibrium.py)
* [Intersection](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/intersection.py)
* [Lu Decomposition](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/lu_decomposition.py)
* [Newton Forward Interpolation](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/newton_forward_interpolation.py)
* [Newton Method](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/newton_method.py)
* [Newton Raphson](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/newton_raphson.py)
* [Secant Method](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/secant_method.py)
## Backtracking
* [All Combinations](https://github.com/TheAlgorithms/Python/blob/master/backtracking/all_combinations.py)
* [All Permutations](https://github.com/TheAlgorithms/Python/blob/master/backtracking/all_permutations.py)
* [All Subsequences](https://github.com/TheAlgorithms/Python/blob/master/backtracking/all_subsequences.py)
* [Coloring](https://github.com/TheAlgorithms/Python/blob/master/backtracking/coloring.py)
* [Hamiltonian Cycle](https://github.com/TheAlgorithms/Python/blob/master/backtracking/hamiltonian_cycle.py)
* [Knight Tour](https://github.com/TheAlgorithms/Python/blob/master/backtracking/knight_tour.py)
* [Minimax](https://github.com/TheAlgorithms/Python/blob/master/backtracking/minimax.py)
* [N Queens](https://github.com/TheAlgorithms/Python/blob/master/backtracking/n_queens.py)
* [N Queens Math](https://github.com/TheAlgorithms/Python/blob/master/backtracking/n_queens_math.py)
* [Rat In Maze](https://github.com/TheAlgorithms/Python/blob/master/backtracking/rat_in_maze.py)
* [Sudoku](https://github.com/TheAlgorithms/Python/blob/master/backtracking/sudoku.py)
* [Sum Of Subsets](https://github.com/TheAlgorithms/Python/blob/master/backtracking/sum_of_subsets.py)
## Bit Manipulation
* [Binary And Operator](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_and_operator.py)
* [Binary Count Setbits](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_count_setbits.py)
* [Binary Count Trailing Zeros](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_count_trailing_zeros.py)
* [Binary Or Operator](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_or_operator.py)
* [Binary Shifts](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_shifts.py)
* [Binary Twos Complement](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_twos_complement.py)
* [Binary Xor Operator](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_xor_operator.py)
* [Count Number Of One Bits](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/count_number_of_one_bits.py)
* [Reverse Bits](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/reverse_bits.py)
* [Single Bit Manipulation Operations](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/single_bit_manipulation_operations.py)
## Blockchain
* [Chinese Remainder Theorem](https://github.com/TheAlgorithms/Python/blob/master/blockchain/chinese_remainder_theorem.py)
* [Diophantine Equation](https://github.com/TheAlgorithms/Python/blob/master/blockchain/diophantine_equation.py)
* [Modular Division](https://github.com/TheAlgorithms/Python/blob/master/blockchain/modular_division.py)
## Boolean Algebra
* [Quine Mc Cluskey](https://github.com/TheAlgorithms/Python/blob/master/boolean_algebra/quine_mc_cluskey.py)
## Cellular Automata
* [Conways Game Of Life](https://github.com/TheAlgorithms/Python/blob/master/cellular_automata/conways_game_of_life.py)
* [One Dimensional](https://github.com/TheAlgorithms/Python/blob/master/cellular_automata/one_dimensional.py)
## Ciphers
* [A1Z26](https://github.com/TheAlgorithms/Python/blob/master/ciphers/a1z26.py)
* [Affine Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/affine_cipher.py)
* [Atbash](https://github.com/TheAlgorithms/Python/blob/master/ciphers/atbash.py)
* [Base16](https://github.com/TheAlgorithms/Python/blob/master/ciphers/base16.py)
* [Base32](https://github.com/TheAlgorithms/Python/blob/master/ciphers/base32.py)
* [Base64 Encoding](https://github.com/TheAlgorithms/Python/blob/master/ciphers/base64_encoding.py)
* [Base85](https://github.com/TheAlgorithms/Python/blob/master/ciphers/base85.py)
* [Beaufort Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/beaufort_cipher.py)
* [Brute Force Caesar Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/brute_force_caesar_cipher.py)
* [Caesar Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/caesar_cipher.py)
* [Cryptomath Module](https://github.com/TheAlgorithms/Python/blob/master/ciphers/cryptomath_module.py)
* [Decrypt Caesar With Chi Squared](https://github.com/TheAlgorithms/Python/blob/master/ciphers/decrypt_caesar_with_chi_squared.py)
* [Deterministic Miller Rabin](https://github.com/TheAlgorithms/Python/blob/master/ciphers/deterministic_miller_rabin.py)
* [Diffie](https://github.com/TheAlgorithms/Python/blob/master/ciphers/diffie.py)
* [Diffie Hellman](https://github.com/TheAlgorithms/Python/blob/master/ciphers/diffie_hellman.py)
* [Elgamal Key Generator](https://github.com/TheAlgorithms/Python/blob/master/ciphers/elgamal_key_generator.py)
* [Enigma Machine2](https://github.com/TheAlgorithms/Python/blob/master/ciphers/enigma_machine2.py)
* [Hill Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/hill_cipher.py)
* [Mixed Keyword Cypher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/mixed_keyword_cypher.py)
* [Mono Alphabetic Ciphers](https://github.com/TheAlgorithms/Python/blob/master/ciphers/mono_alphabetic_ciphers.py)
* [Morse Code Implementation](https://github.com/TheAlgorithms/Python/blob/master/ciphers/morse_code_implementation.py)
* [Onepad Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/onepad_cipher.py)
* [Playfair Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/playfair_cipher.py)
* [Porta Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/porta_cipher.py)
* [Rabin Miller](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rabin_miller.py)
* [Rail Fence Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rail_fence_cipher.py)
* [Rot13](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rot13.py)
* [Rsa Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rsa_cipher.py)
* [Rsa Factorization](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rsa_factorization.py)
* [Rsa Key Generator](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rsa_key_generator.py)
* [Shuffled Shift Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/shuffled_shift_cipher.py)
* [Simple Keyword Cypher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/simple_keyword_cypher.py)
* [Simple Substitution Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/simple_substitution_cipher.py)
* [Trafid Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/trafid_cipher.py)
* [Transposition Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/transposition_cipher.py)
* [Transposition Cipher Encrypt Decrypt File](https://github.com/TheAlgorithms/Python/blob/master/ciphers/transposition_cipher_encrypt_decrypt_file.py)
* [Vigenere Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/vigenere_cipher.py)
* [Xor Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/xor_cipher.py)
## Compression
* [Burrows Wheeler](https://github.com/TheAlgorithms/Python/blob/master/compression/burrows_wheeler.py)
* [Huffman](https://github.com/TheAlgorithms/Python/blob/master/compression/huffman.py)
* [Lempel Ziv](https://github.com/TheAlgorithms/Python/blob/master/compression/lempel_ziv.py)
* [Lempel Ziv Decompress](https://github.com/TheAlgorithms/Python/blob/master/compression/lempel_ziv_decompress.py)
* [Peak Signal To Noise Ratio](https://github.com/TheAlgorithms/Python/blob/master/compression/peak_signal_to_noise_ratio.py)
## Computer Vision
* [Harriscorner](https://github.com/TheAlgorithms/Python/blob/master/computer_vision/harriscorner.py)
* [Meanthreshold](https://github.com/TheAlgorithms/Python/blob/master/computer_vision/meanthreshold.py)
## Conversions
* [Binary To Decimal](https://github.com/TheAlgorithms/Python/blob/master/conversions/binary_to_decimal.py)
* [Binary To Octal](https://github.com/TheAlgorithms/Python/blob/master/conversions/binary_to_octal.py)
* [Decimal To Any](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_any.py)
* [Decimal To Binary](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_binary.py)
* [Decimal To Binary Recursion](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_binary_recursion.py)
* [Decimal To Hexadecimal](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_hexadecimal.py)
* [Decimal To Octal](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_octal.py)
* [Hexadecimal To Decimal](https://github.com/TheAlgorithms/Python/blob/master/conversions/hexadecimal_to_decimal.py)
* [Molecular Chemistry](https://github.com/TheAlgorithms/Python/blob/master/conversions/molecular_chemistry.py)
* [Octal To Decimal](https://github.com/TheAlgorithms/Python/blob/master/conversions/octal_to_decimal.py)
* [Prefix Conversions](https://github.com/TheAlgorithms/Python/blob/master/conversions/prefix_conversions.py)
* [Roman Numerals](https://github.com/TheAlgorithms/Python/blob/master/conversions/roman_numerals.py)
* [Temperature Conversions](https://github.com/TheAlgorithms/Python/blob/master/conversions/temperature_conversions.py)
* [Weight Conversion](https://github.com/TheAlgorithms/Python/blob/master/conversions/weight_conversion.py)
## Data Structures
* Binary Tree
* [Avl Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/avl_tree.py)
* [Basic Binary Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/basic_binary_tree.py)
* [Binary Search Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/binary_search_tree.py)
* [Binary Search Tree Recursive](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/binary_search_tree_recursive.py)
* [Binary Tree Mirror](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/binary_tree_mirror.py)
* [Binary Tree Traversals](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/binary_tree_traversals.py)
* [Fenwick Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/fenwick_tree.py)
* [Lazy Segment Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/lazy_segment_tree.py)
* [Lowest Common Ancestor](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/lowest_common_ancestor.py)
* [Merge Two Binary Trees](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/merge_two_binary_trees.py)
* [Non Recursive Segment Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/non_recursive_segment_tree.py)
* [Number Of Possible Binary Trees](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/number_of_possible_binary_trees.py)
* [Red Black Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/red_black_tree.py)
* [Segment Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/segment_tree.py)
* [Segment Tree Other](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/segment_tree_other.py)
* [Treap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/treap.py)
* Disjoint Set
* [Alternate Disjoint Set](https://github.com/TheAlgorithms/Python/blob/master/data_structures/disjoint_set/alternate_disjoint_set.py)
* [Disjoint Set](https://github.com/TheAlgorithms/Python/blob/master/data_structures/disjoint_set/disjoint_set.py)
* Hashing
* [Double Hash](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/double_hash.py)
* [Hash Table](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/hash_table.py)
* [Hash Table With Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/hash_table_with_linked_list.py)
* Number Theory
* [Prime Numbers](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/number_theory/prime_numbers.py)
* [Quadratic Probing](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/quadratic_probing.py)
* Heap
* [Binomial Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/binomial_heap.py)
* [Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/heap.py)
* [Heap Generic](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/heap_generic.py)
* [Max Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/max_heap.py)
* [Min Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/min_heap.py)
* [Randomized Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/randomized_heap.py)
* [Skew Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/skew_heap.py)
* Linked List
* [Circular Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/circular_linked_list.py)
* [Deque Doubly](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/deque_doubly.py)
* [Doubly Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/doubly_linked_list.py)
* [Doubly Linked List Two](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/doubly_linked_list_two.py)
* [From Sequence](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/from_sequence.py)
* [Has Loop](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/has_loop.py)
* [Is Palindrome](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/is_palindrome.py)
* [Merge Two Lists](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/merge_two_lists.py)
* [Middle Element Of Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/middle_element_of_linked_list.py)
* [Print Reverse](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/print_reverse.py)
* [Singly Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/singly_linked_list.py)
* [Skip List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/skip_list.py)
* [Swap Nodes](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/swap_nodes.py)
* Queue
* [Circular Queue](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/circular_queue.py)
* [Double Ended Queue](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/double_ended_queue.py)
* [Linked Queue](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/linked_queue.py)
* [Priority Queue Using List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/priority_queue_using_list.py)
* [Queue On List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/queue_on_list.py)
* [Queue On Pseudo Stack](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/queue_on_pseudo_stack.py)
* Stacks
* [Balanced Parentheses](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/balanced_parentheses.py)
* [Dijkstras Two Stack Algorithm](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/dijkstras_two_stack_algorithm.py)
* [Evaluate Postfix Notations](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/evaluate_postfix_notations.py)
* [Infix To Postfix Conversion](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/infix_to_postfix_conversion.py)
* [Infix To Prefix Conversion](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/infix_to_prefix_conversion.py)
* [Linked Stack](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/linked_stack.py)
* [Next Greater Element](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/next_greater_element.py)
* [Postfix Evaluation](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/postfix_evaluation.py)
* [Prefix Evaluation](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/prefix_evaluation.py)
* [Stack](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/stack.py)
* [Stack Using Dll](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/stack_using_dll.py)
* [Stock Span Problem](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/stock_span_problem.py)
* Trie
* [Trie](https://github.com/TheAlgorithms/Python/blob/master/data_structures/trie/trie.py)
## Digital Image Processing
* [Change Brightness](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/change_brightness.py)
* [Change Contrast](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/change_contrast.py)
* [Convert To Negative](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/convert_to_negative.py)
* Dithering
* [Burkes](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/dithering/burkes.py)
* Edge Detection
* [Canny](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/edge_detection/canny.py)
* Filters
* [Bilateral Filter](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/bilateral_filter.py)
* [Convolve](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/convolve.py)
* [Gaussian Filter](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/gaussian_filter.py)
* [Median Filter](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/median_filter.py)
* [Sobel Filter](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/sobel_filter.py)
* Histogram Equalization
* [Histogram Stretch](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/histogram_equalization/histogram_stretch.py)
* [Index Calculation](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/index_calculation.py)
* Resize
* [Resize](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/resize/resize.py)
* Rotation
* [Rotation](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/rotation/rotation.py)
* [Sepia](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/sepia.py)
* [Test Digital Image Processing](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/test_digital_image_processing.py)
## Divide And Conquer
* [Closest Pair Of Points](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/closest_pair_of_points.py)
* [Convex Hull](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/convex_hull.py)
* [Heaps Algorithm](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/heaps_algorithm.py)
* [Heaps Algorithm Iterative](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/heaps_algorithm_iterative.py)
* [Inversions](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/inversions.py)
* [Kth Order Statistic](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/kth_order_statistic.py)
* [Max Difference Pair](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/max_difference_pair.py)
* [Max Subarray Sum](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/max_subarray_sum.py)
* [Mergesort](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/mergesort.py)
* [Peak](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/peak.py)
* [Power](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/power.py)
* [Strassen Matrix Multiplication](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/strassen_matrix_multiplication.py)
## Dynamic Programming
* [Abbreviation](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/abbreviation.py)
* [Bitmask](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/bitmask.py)
* [Climbing Stairs](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/climbing_stairs.py)
* [Edit Distance](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/edit_distance.py)
* [Factorial](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/factorial.py)
* [Fast Fibonacci](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/fast_fibonacci.py)
* [Fibonacci](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/fibonacci.py)
* [Floyd Warshall](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/floyd_warshall.py)
* [Fractional Knapsack](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/fractional_knapsack.py)
* [Fractional Knapsack 2](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/fractional_knapsack_2.py)
* [Integer Partition](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/integer_partition.py)
* [Iterating Through Submasks](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/iterating_through_submasks.py)
* [Knapsack](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/knapsack.py)
* [Longest Common Subsequence](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/longest_common_subsequence.py)
* [Longest Increasing Subsequence](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/longest_increasing_subsequence.py)
* [Longest Increasing Subsequence O(Nlogn)](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/longest_increasing_subsequence_o(nlogn).py)
* [Longest Sub Array](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/longest_sub_array.py)
* [Matrix Chain Order](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/matrix_chain_order.py)
* [Max Non Adjacent Sum](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/max_non_adjacent_sum.py)
* [Max Sub Array](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/max_sub_array.py)
* [Max Sum Contiguous Subsequence](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/max_sum_contiguous_subsequence.py)
* [Minimum Coin Change](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/minimum_coin_change.py)
* [Minimum Cost Path](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/minimum_cost_path.py)
* [Minimum Partition](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/minimum_partition.py)
* [Minimum Steps To One](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/minimum_steps_to_one.py)
* [Optimal Binary Search Tree](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/optimal_binary_search_tree.py)
* [Rod Cutting](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/rod_cutting.py)
* [Subset Generation](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/subset_generation.py)
* [Sum Of Subset](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/sum_of_subset.py)
## Electronics
* [Electric Power](https://github.com/TheAlgorithms/Python/blob/master/electronics/electric_power.py)
* [Ohms Law](https://github.com/TheAlgorithms/Python/blob/master/electronics/ohms_law.py)
## File Transfer
* [Receive File](https://github.com/TheAlgorithms/Python/blob/master/file_transfer/receive_file.py)
* [Send File](https://github.com/TheAlgorithms/Python/blob/master/file_transfer/send_file.py)
* Tests
* [Test Send File](https://github.com/TheAlgorithms/Python/blob/master/file_transfer/tests/test_send_file.py)
## Fuzzy Logic
* [Fuzzy Operations](https://github.com/TheAlgorithms/Python/blob/master/fuzzy_logic/fuzzy_operations.py)
## Genetic Algorithm
* [Basic String](https://github.com/TheAlgorithms/Python/blob/master/genetic_algorithm/basic_string.py)
## Geodesy
* [Haversine Distance](https://github.com/TheAlgorithms/Python/blob/master/geodesy/haversine_distance.py)
* [Lamberts Ellipsoidal Distance](https://github.com/TheAlgorithms/Python/blob/master/geodesy/lamberts_ellipsoidal_distance.py)
## Graphics
* [Bezier Curve](https://github.com/TheAlgorithms/Python/blob/master/graphics/bezier_curve.py)
* [Koch Snowflake](https://github.com/TheAlgorithms/Python/blob/master/graphics/koch_snowflake.py)
* [Mandelbrot](https://github.com/TheAlgorithms/Python/blob/master/graphics/mandelbrot.py)
* [Vector3 For 2D Rendering](https://github.com/TheAlgorithms/Python/blob/master/graphics/vector3_for_2d_rendering.py)
## Graphs
* [A Star](https://github.com/TheAlgorithms/Python/blob/master/graphs/a_star.py)
* [Articulation Points](https://github.com/TheAlgorithms/Python/blob/master/graphs/articulation_points.py)
* [Basic Graphs](https://github.com/TheAlgorithms/Python/blob/master/graphs/basic_graphs.py)
* [Bellman Ford](https://github.com/TheAlgorithms/Python/blob/master/graphs/bellman_ford.py)
* [Bfs Shortest Path](https://github.com/TheAlgorithms/Python/blob/master/graphs/bfs_shortest_path.py)
* [Bfs Zero One Shortest Path](https://github.com/TheAlgorithms/Python/blob/master/graphs/bfs_zero_one_shortest_path.py)
* [Bidirectional A Star](https://github.com/TheAlgorithms/Python/blob/master/graphs/bidirectional_a_star.py)
* [Bidirectional Breadth First Search](https://github.com/TheAlgorithms/Python/blob/master/graphs/bidirectional_breadth_first_search.py)
* [Breadth First Search](https://github.com/TheAlgorithms/Python/blob/master/graphs/breadth_first_search.py)
* [Breadth First Search 2](https://github.com/TheAlgorithms/Python/blob/master/graphs/breadth_first_search_2.py)
* [Breadth First Search Shortest Path](https://github.com/TheAlgorithms/Python/blob/master/graphs/breadth_first_search_shortest_path.py)
* [Check Bipartite Graph Bfs](https://github.com/TheAlgorithms/Python/blob/master/graphs/check_bipartite_graph_bfs.py)
* [Check Bipartite Graph Dfs](https://github.com/TheAlgorithms/Python/blob/master/graphs/check_bipartite_graph_dfs.py)
* [Connected Components](https://github.com/TheAlgorithms/Python/blob/master/graphs/connected_components.py)
* [Depth First Search](https://github.com/TheAlgorithms/Python/blob/master/graphs/depth_first_search.py)
* [Depth First Search 2](https://github.com/TheAlgorithms/Python/blob/master/graphs/depth_first_search_2.py)
* [Dijkstra](https://github.com/TheAlgorithms/Python/blob/master/graphs/dijkstra.py)
* [Dijkstra 2](https://github.com/TheAlgorithms/Python/blob/master/graphs/dijkstra_2.py)
* [Dijkstra Algorithm](https://github.com/TheAlgorithms/Python/blob/master/graphs/dijkstra_algorithm.py)
* [Dinic](https://github.com/TheAlgorithms/Python/blob/master/graphs/dinic.py)
* [Directed And Undirected (Weighted) Graph](https://github.com/TheAlgorithms/Python/blob/master/graphs/directed_and_undirected_(weighted)_graph.py)
* [Edmonds Karp Multiple Source And Sink](https://github.com/TheAlgorithms/Python/blob/master/graphs/edmonds_karp_multiple_source_and_sink.py)
* [Eulerian Path And Circuit For Undirected Graph](https://github.com/TheAlgorithms/Python/blob/master/graphs/eulerian_path_and_circuit_for_undirected_graph.py)
* [Even Tree](https://github.com/TheAlgorithms/Python/blob/master/graphs/even_tree.py)
* [Finding Bridges](https://github.com/TheAlgorithms/Python/blob/master/graphs/finding_bridges.py)
* [Frequent Pattern Graph Miner](https://github.com/TheAlgorithms/Python/blob/master/graphs/frequent_pattern_graph_miner.py)
* [G Topological Sort](https://github.com/TheAlgorithms/Python/blob/master/graphs/g_topological_sort.py)
* [Gale Shapley Bigraph](https://github.com/TheAlgorithms/Python/blob/master/graphs/gale_shapley_bigraph.py)
* [Graph List](https://github.com/TheAlgorithms/Python/blob/master/graphs/graph_list.py)
* [Graph Matrix](https://github.com/TheAlgorithms/Python/blob/master/graphs/graph_matrix.py)
* [Graphs Floyd Warshall](https://github.com/TheAlgorithms/Python/blob/master/graphs/graphs_floyd_warshall.py)
* [Greedy Best First](https://github.com/TheAlgorithms/Python/blob/master/graphs/greedy_best_first.py)
* [Kahns Algorithm Long](https://github.com/TheAlgorithms/Python/blob/master/graphs/kahns_algorithm_long.py)
* [Kahns Algorithm Topo](https://github.com/TheAlgorithms/Python/blob/master/graphs/kahns_algorithm_topo.py)
* [Karger](https://github.com/TheAlgorithms/Python/blob/master/graphs/karger.py)
* [Minimum Spanning Tree Boruvka](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_boruvka.py)
* [Minimum Spanning Tree Kruskal](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_kruskal.py)
* [Minimum Spanning Tree Kruskal2](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_kruskal2.py)
* [Minimum Spanning Tree Prims](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_prims.py)
* [Minimum Spanning Tree Prims2](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_prims2.py)
* [Multi Heuristic Astar](https://github.com/TheAlgorithms/Python/blob/master/graphs/multi_heuristic_astar.py)
* [Page Rank](https://github.com/TheAlgorithms/Python/blob/master/graphs/page_rank.py)
* [Prim](https://github.com/TheAlgorithms/Python/blob/master/graphs/prim.py)
* [Scc Kosaraju](https://github.com/TheAlgorithms/Python/blob/master/graphs/scc_kosaraju.py)
* [Strongly Connected Components](https://github.com/TheAlgorithms/Python/blob/master/graphs/strongly_connected_components.py)
* [Tarjans Scc](https://github.com/TheAlgorithms/Python/blob/master/graphs/tarjans_scc.py)
* Tests
* [Test Min Spanning Tree Kruskal](https://github.com/TheAlgorithms/Python/blob/master/graphs/tests/test_min_spanning_tree_kruskal.py)
* [Test Min Spanning Tree Prim](https://github.com/TheAlgorithms/Python/blob/master/graphs/tests/test_min_spanning_tree_prim.py)
## Hashes
* [Adler32](https://github.com/TheAlgorithms/Python/blob/master/hashes/adler32.py)
* [Chaos Machine](https://github.com/TheAlgorithms/Python/blob/master/hashes/chaos_machine.py)
* [Djb2](https://github.com/TheAlgorithms/Python/blob/master/hashes/djb2.py)
* [Enigma Machine](https://github.com/TheAlgorithms/Python/blob/master/hashes/enigma_machine.py)
* [Hamming Code](https://github.com/TheAlgorithms/Python/blob/master/hashes/hamming_code.py)
* [Md5](https://github.com/TheAlgorithms/Python/blob/master/hashes/md5.py)
* [Sdbm](https://github.com/TheAlgorithms/Python/blob/master/hashes/sdbm.py)
* [Sha1](https://github.com/TheAlgorithms/Python/blob/master/hashes/sha1.py)
## Knapsack
* [Greedy Knapsack](https://github.com/TheAlgorithms/Python/blob/master/knapsack/greedy_knapsack.py)
* [Knapsack](https://github.com/TheAlgorithms/Python/blob/master/knapsack/knapsack.py)
* Tests
* [Test Greedy Knapsack](https://github.com/TheAlgorithms/Python/blob/master/knapsack/tests/test_greedy_knapsack.py)
* [Test Knapsack](https://github.com/TheAlgorithms/Python/blob/master/knapsack/tests/test_knapsack.py)
## Linear Algebra
* Src
* [Conjugate Gradient](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/conjugate_gradient.py)
* [Lib](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/lib.py)
* [Polynom For Points](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/polynom_for_points.py)
* [Power Iteration](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/power_iteration.py)
* [Rayleigh Quotient](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/rayleigh_quotient.py)
* [Test Linear Algebra](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/test_linear_algebra.py)
* [Transformations 2D](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/transformations_2d.py)
## Machine Learning
* [Astar](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/astar.py)
* [Data Transformations](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/data_transformations.py)
* [Decision Tree](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/decision_tree.py)
* Forecasting
* [Run](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/forecasting/run.py)
* [Gaussian Naive Bayes](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gaussian_naive_bayes.py)
* [Gradient Boosting Regressor](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_boosting_regressor.py)
* [Gradient Descent](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_descent.py)
* [K Means Clust](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_means_clust.py)
* [K Nearest Neighbours](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_nearest_neighbours.py)
* [Knn Sklearn](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/knn_sklearn.py)
* [Linear Discriminant Analysis](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/linear_discriminant_analysis.py)
* [Linear Regression](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/linear_regression.py)
* [Logistic Regression](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/logistic_regression.py)
* [Multilayer Perceptron Classifier](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/multilayer_perceptron_classifier.py)
* [Polymonial Regression](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/polymonial_regression.py)
* [Random Forest Classifier](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/random_forest_classifier.py)
* [Random Forest Regressor](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/random_forest_regressor.py)
* [Scoring Functions](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/scoring_functions.py)
* [Sequential Minimum Optimization](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/sequential_minimum_optimization.py)
* [Similarity Search](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/similarity_search.py)
* [Support Vector Machines](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/support_vector_machines.py)
* [Word Frequency Functions](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/word_frequency_functions.py)
## Maths
* [3N Plus 1](https://github.com/TheAlgorithms/Python/blob/master/maths/3n_plus_1.py)
* [Abs](https://github.com/TheAlgorithms/Python/blob/master/maths/abs.py)
* [Abs Max](https://github.com/TheAlgorithms/Python/blob/master/maths/abs_max.py)
* [Abs Min](https://github.com/TheAlgorithms/Python/blob/master/maths/abs_min.py)
* [Add](https://github.com/TheAlgorithms/Python/blob/master/maths/add.py)
* [Aliquot Sum](https://github.com/TheAlgorithms/Python/blob/master/maths/aliquot_sum.py)
* [Allocation Number](https://github.com/TheAlgorithms/Python/blob/master/maths/allocation_number.py)
* [Area](https://github.com/TheAlgorithms/Python/blob/master/maths/area.py)
* [Area Under Curve](https://github.com/TheAlgorithms/Python/blob/master/maths/area_under_curve.py)
* [Armstrong Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/armstrong_numbers.py)
* [Average Mean](https://github.com/TheAlgorithms/Python/blob/master/maths/average_mean.py)
* [Average Median](https://github.com/TheAlgorithms/Python/blob/master/maths/average_median.py)
* [Average Mode](https://github.com/TheAlgorithms/Python/blob/master/maths/average_mode.py)
* [Bailey Borwein Plouffe](https://github.com/TheAlgorithms/Python/blob/master/maths/bailey_borwein_plouffe.py)
* [Basic Maths](https://github.com/TheAlgorithms/Python/blob/master/maths/basic_maths.py)
* [Binary Exp Mod](https://github.com/TheAlgorithms/Python/blob/master/maths/binary_exp_mod.py)
* [Binary Exponentiation](https://github.com/TheAlgorithms/Python/blob/master/maths/binary_exponentiation.py)
* [Binomial Coefficient](https://github.com/TheAlgorithms/Python/blob/master/maths/binomial_coefficient.py)
* [Binomial Distribution](https://github.com/TheAlgorithms/Python/blob/master/maths/binomial_distribution.py)
* [Bisection](https://github.com/TheAlgorithms/Python/blob/master/maths/bisection.py)
* [Ceil](https://github.com/TheAlgorithms/Python/blob/master/maths/ceil.py)
* [Chudnovsky Algorithm](https://github.com/TheAlgorithms/Python/blob/master/maths/chudnovsky_algorithm.py)
* [Collatz Sequence](https://github.com/TheAlgorithms/Python/blob/master/maths/collatz_sequence.py)
* [Combinations](https://github.com/TheAlgorithms/Python/blob/master/maths/combinations.py)
* [Decimal Isolate](https://github.com/TheAlgorithms/Python/blob/master/maths/decimal_isolate.py)
* [Entropy](https://github.com/TheAlgorithms/Python/blob/master/maths/entropy.py)
* [Euclidean Distance](https://github.com/TheAlgorithms/Python/blob/master/maths/euclidean_distance.py)
* [Eulers Totient](https://github.com/TheAlgorithms/Python/blob/master/maths/eulers_totient.py)
* [Explicit Euler](https://github.com/TheAlgorithms/Python/blob/master/maths/explicit_euler.py)
* [Extended Euclidean Algorithm](https://github.com/TheAlgorithms/Python/blob/master/maths/extended_euclidean_algorithm.py)
* [Factorial Iterative](https://github.com/TheAlgorithms/Python/blob/master/maths/factorial_iterative.py)
* [Factorial Python](https://github.com/TheAlgorithms/Python/blob/master/maths/factorial_python.py)
* [Factorial Recursive](https://github.com/TheAlgorithms/Python/blob/master/maths/factorial_recursive.py)
* [Factors](https://github.com/TheAlgorithms/Python/blob/master/maths/factors.py)
* [Fermat Little Theorem](https://github.com/TheAlgorithms/Python/blob/master/maths/fermat_little_theorem.py)
* [Fibonacci](https://github.com/TheAlgorithms/Python/blob/master/maths/fibonacci.py)
* [Fibonacci Sequence Recursion](https://github.com/TheAlgorithms/Python/blob/master/maths/fibonacci_sequence_recursion.py)
* [Find Max](https://github.com/TheAlgorithms/Python/blob/master/maths/find_max.py)
* [Find Max Recursion](https://github.com/TheAlgorithms/Python/blob/master/maths/find_max_recursion.py)
* [Find Min](https://github.com/TheAlgorithms/Python/blob/master/maths/find_min.py)
* [Find Min Recursion](https://github.com/TheAlgorithms/Python/blob/master/maths/find_min_recursion.py)
* [Floor](https://github.com/TheAlgorithms/Python/blob/master/maths/floor.py)
* [Gamma](https://github.com/TheAlgorithms/Python/blob/master/maths/gamma.py)
* [Gaussian](https://github.com/TheAlgorithms/Python/blob/master/maths/gaussian.py)
* [Greatest Common Divisor](https://github.com/TheAlgorithms/Python/blob/master/maths/greatest_common_divisor.py)
* [Hardy Ramanujanalgo](https://github.com/TheAlgorithms/Python/blob/master/maths/hardy_ramanujanalgo.py)
* [Is Square Free](https://github.com/TheAlgorithms/Python/blob/master/maths/is_square_free.py)
* [Jaccard Similarity](https://github.com/TheAlgorithms/Python/blob/master/maths/jaccard_similarity.py)
* [Kadanes](https://github.com/TheAlgorithms/Python/blob/master/maths/kadanes.py)
* [Karatsuba](https://github.com/TheAlgorithms/Python/blob/master/maths/karatsuba.py)
* [Krishnamurthy Number](https://github.com/TheAlgorithms/Python/blob/master/maths/krishnamurthy_number.py)
* [Kth Lexicographic Permutation](https://github.com/TheAlgorithms/Python/blob/master/maths/kth_lexicographic_permutation.py)
* [Largest Of Very Large Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/largest_of_very_large_numbers.py)
* [Least Common Multiple](https://github.com/TheAlgorithms/Python/blob/master/maths/least_common_multiple.py)
* [Line Length](https://github.com/TheAlgorithms/Python/blob/master/maths/line_length.py)
* [Lucas Lehmer Primality Test](https://github.com/TheAlgorithms/Python/blob/master/maths/lucas_lehmer_primality_test.py)
* [Lucas Series](https://github.com/TheAlgorithms/Python/blob/master/maths/lucas_series.py)
* [Matrix Exponentiation](https://github.com/TheAlgorithms/Python/blob/master/maths/matrix_exponentiation.py)
* [Miller Rabin](https://github.com/TheAlgorithms/Python/blob/master/maths/miller_rabin.py)
* [Mobius Function](https://github.com/TheAlgorithms/Python/blob/master/maths/mobius_function.py)
* [Modular Exponential](https://github.com/TheAlgorithms/Python/blob/master/maths/modular_exponential.py)
* [Monte Carlo](https://github.com/TheAlgorithms/Python/blob/master/maths/monte_carlo.py)
* [Monte Carlo Dice](https://github.com/TheAlgorithms/Python/blob/master/maths/monte_carlo_dice.py)
* [Newton Raphson](https://github.com/TheAlgorithms/Python/blob/master/maths/newton_raphson.py)
* [Number Of Digits](https://github.com/TheAlgorithms/Python/blob/master/maths/number_of_digits.py)
* [Numerical Integration](https://github.com/TheAlgorithms/Python/blob/master/maths/numerical_integration.py)
* [Perfect Cube](https://github.com/TheAlgorithms/Python/blob/master/maths/perfect_cube.py)
* [Perfect Number](https://github.com/TheAlgorithms/Python/blob/master/maths/perfect_number.py)
* [Perfect Square](https://github.com/TheAlgorithms/Python/blob/master/maths/perfect_square.py)
* [Pi Monte Carlo Estimation](https://github.com/TheAlgorithms/Python/blob/master/maths/pi_monte_carlo_estimation.py)
* [Polynomial Evaluation](https://github.com/TheAlgorithms/Python/blob/master/maths/polynomial_evaluation.py)
* [Power Using Recursion](https://github.com/TheAlgorithms/Python/blob/master/maths/power_using_recursion.py)
* [Prime Check](https://github.com/TheAlgorithms/Python/blob/master/maths/prime_check.py)
* [Prime Factors](https://github.com/TheAlgorithms/Python/blob/master/maths/prime_factors.py)
* [Prime Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/prime_numbers.py)
* [Prime Sieve Eratosthenes](https://github.com/TheAlgorithms/Python/blob/master/maths/prime_sieve_eratosthenes.py)
* [Pythagoras](https://github.com/TheAlgorithms/Python/blob/master/maths/pythagoras.py)
* [Qr Decomposition](https://github.com/TheAlgorithms/Python/blob/master/maths/qr_decomposition.py)
* [Quadratic Equations Complex Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/quadratic_equations_complex_numbers.py)
* [Radians](https://github.com/TheAlgorithms/Python/blob/master/maths/radians.py)
* [Radix2 Fft](https://github.com/TheAlgorithms/Python/blob/master/maths/radix2_fft.py)
* [Relu](https://github.com/TheAlgorithms/Python/blob/master/maths/relu.py)
* [Runge Kutta](https://github.com/TheAlgorithms/Python/blob/master/maths/runge_kutta.py)
* [Segmented Sieve](https://github.com/TheAlgorithms/Python/blob/master/maths/segmented_sieve.py)
* Series
* [Arithmetic Mean](https://github.com/TheAlgorithms/Python/blob/master/maths/series/arithmetic_mean.py)
* [Geometric Mean](https://github.com/TheAlgorithms/Python/blob/master/maths/series/geometric_mean.py)
* [Geometric Series](https://github.com/TheAlgorithms/Python/blob/master/maths/series/geometric_series.py)
* [Harmonic Series](https://github.com/TheAlgorithms/Python/blob/master/maths/series/harmonic_series.py)
* [P Series](https://github.com/TheAlgorithms/Python/blob/master/maths/series/p_series.py)
* [Sieve Of Eratosthenes](https://github.com/TheAlgorithms/Python/blob/master/maths/sieve_of_eratosthenes.py)
* [Sigmoid](https://github.com/TheAlgorithms/Python/blob/master/maths/sigmoid.py)
* [Simpson Rule](https://github.com/TheAlgorithms/Python/blob/master/maths/simpson_rule.py)
* [Softmax](https://github.com/TheAlgorithms/Python/blob/master/maths/softmax.py)
* [Square Root](https://github.com/TheAlgorithms/Python/blob/master/maths/square_root.py)
* [Sum Of Arithmetic Series](https://github.com/TheAlgorithms/Python/blob/master/maths/sum_of_arithmetic_series.py)
* [Sum Of Digits](https://github.com/TheAlgorithms/Python/blob/master/maths/sum_of_digits.py)
* [Sum Of Geometric Progression](https://github.com/TheAlgorithms/Python/blob/master/maths/sum_of_geometric_progression.py)
* [Test Prime Check](https://github.com/TheAlgorithms/Python/blob/master/maths/test_prime_check.py)
* [Trapezoidal Rule](https://github.com/TheAlgorithms/Python/blob/master/maths/trapezoidal_rule.py)
* [Ugly Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/ugly_numbers.py)
* [Volume](https://github.com/TheAlgorithms/Python/blob/master/maths/volume.py)
* [Zellers Congruence](https://github.com/TheAlgorithms/Python/blob/master/maths/zellers_congruence.py)
## Matrix
* [Count Islands In Matrix](https://github.com/TheAlgorithms/Python/blob/master/matrix/count_islands_in_matrix.py)
* [Inverse Of Matrix](https://github.com/TheAlgorithms/Python/blob/master/matrix/inverse_of_matrix.py)
* [Matrix Class](https://github.com/TheAlgorithms/Python/blob/master/matrix/matrix_class.py)
* [Matrix Operation](https://github.com/TheAlgorithms/Python/blob/master/matrix/matrix_operation.py)
* [Nth Fibonacci Using Matrix Exponentiation](https://github.com/TheAlgorithms/Python/blob/master/matrix/nth_fibonacci_using_matrix_exponentiation.py)
* [Rotate Matrix](https://github.com/TheAlgorithms/Python/blob/master/matrix/rotate_matrix.py)
* [Searching In Sorted Matrix](https://github.com/TheAlgorithms/Python/blob/master/matrix/searching_in_sorted_matrix.py)
* [Sherman Morrison](https://github.com/TheAlgorithms/Python/blob/master/matrix/sherman_morrison.py)
* [Spiral Print](https://github.com/TheAlgorithms/Python/blob/master/matrix/spiral_print.py)
* Tests
* [Test Matrix Operation](https://github.com/TheAlgorithms/Python/blob/master/matrix/tests/test_matrix_operation.py)
## Networking Flow
* [Ford Fulkerson](https://github.com/TheAlgorithms/Python/blob/master/networking_flow/ford_fulkerson.py)
* [Minimum Cut](https://github.com/TheAlgorithms/Python/blob/master/networking_flow/minimum_cut.py)
## Neural Network
* [2 Hidden Layers Neural Network](https://github.com/TheAlgorithms/Python/blob/master/neural_network/2_hidden_layers_neural_network.py)
* [Back Propagation Neural Network](https://github.com/TheAlgorithms/Python/blob/master/neural_network/back_propagation_neural_network.py)
* [Convolution Neural Network](https://github.com/TheAlgorithms/Python/blob/master/neural_network/convolution_neural_network.py)
* [Perceptron](https://github.com/TheAlgorithms/Python/blob/master/neural_network/perceptron.py)
## Other
* [Activity Selection](https://github.com/TheAlgorithms/Python/blob/master/other/activity_selection.py)
* [Anagrams](https://github.com/TheAlgorithms/Python/blob/master/other/anagrams.py)
* [Autocomplete Using Trie](https://github.com/TheAlgorithms/Python/blob/master/other/autocomplete_using_trie.py)
* [Binary Exponentiation](https://github.com/TheAlgorithms/Python/blob/master/other/binary_exponentiation.py)
* [Binary Exponentiation 2](https://github.com/TheAlgorithms/Python/blob/master/other/binary_exponentiation_2.py)
* [Davis–Putnam–Logemann–Loveland](https://github.com/TheAlgorithms/Python/blob/master/other/davis–putnam–logemann–loveland.py)
* [Detecting English Programmatically](https://github.com/TheAlgorithms/Python/blob/master/other/detecting_english_programmatically.py)
* [Dijkstra Bankers Algorithm](https://github.com/TheAlgorithms/Python/blob/master/other/dijkstra_bankers_algorithm.py)
* [Doomsday](https://github.com/TheAlgorithms/Python/blob/master/other/doomsday.py)
* [Euclidean Gcd](https://github.com/TheAlgorithms/Python/blob/master/other/euclidean_gcd.py)
* [Fischer Yates Shuffle](https://github.com/TheAlgorithms/Python/blob/master/other/fischer_yates_shuffle.py)
* [Frequency Finder](https://github.com/TheAlgorithms/Python/blob/master/other/frequency_finder.py)
* [Game Of Life](https://github.com/TheAlgorithms/Python/blob/master/other/game_of_life.py)
* [Gauss Easter](https://github.com/TheAlgorithms/Python/blob/master/other/gauss_easter.py)
* [Graham Scan](https://github.com/TheAlgorithms/Python/blob/master/other/graham_scan.py)
* [Greedy](https://github.com/TheAlgorithms/Python/blob/master/other/greedy.py)
* [Integeration By Simpson Approx](https://github.com/TheAlgorithms/Python/blob/master/other/integeration_by_simpson_approx.py)
* [Largest Subarray Sum](https://github.com/TheAlgorithms/Python/blob/master/other/largest_subarray_sum.py)
* [Least Recently Used](https://github.com/TheAlgorithms/Python/blob/master/other/least_recently_used.py)
* [Lfu Cache](https://github.com/TheAlgorithms/Python/blob/master/other/lfu_cache.py)
* [Linear Congruential Generator](https://github.com/TheAlgorithms/Python/blob/master/other/linear_congruential_generator.py)
* [Lru Cache](https://github.com/TheAlgorithms/Python/blob/master/other/lru_cache.py)
* [Magicdiamondpattern](https://github.com/TheAlgorithms/Python/blob/master/other/magicdiamondpattern.py)
* [Markov Chain](https://github.com/TheAlgorithms/Python/blob/master/other/markov_chain.py)
* [Max Sum Sliding Window](https://github.com/TheAlgorithms/Python/blob/master/other/max_sum_sliding_window.py)
* [Median Of Two Arrays](https://github.com/TheAlgorithms/Python/blob/master/other/median_of_two_arrays.py)
* [Nested Brackets](https://github.com/TheAlgorithms/Python/blob/master/other/nested_brackets.py)
* [Palindrome](https://github.com/TheAlgorithms/Python/blob/master/other/palindrome.py)
* [Password Generator](https://github.com/TheAlgorithms/Python/blob/master/other/password_generator.py)
* [Primelib](https://github.com/TheAlgorithms/Python/blob/master/other/primelib.py)
* [Scoring Algorithm](https://github.com/TheAlgorithms/Python/blob/master/other/scoring_algorithm.py)
* [Sdes](https://github.com/TheAlgorithms/Python/blob/master/other/sdes.py)
* [Sierpinski Triangle](https://github.com/TheAlgorithms/Python/blob/master/other/sierpinski_triangle.py)
* [Tower Of Hanoi](https://github.com/TheAlgorithms/Python/blob/master/other/tower_of_hanoi.py)
* [Triplet Sum](https://github.com/TheAlgorithms/Python/blob/master/other/triplet_sum.py)
* [Two Pointer](https://github.com/TheAlgorithms/Python/blob/master/other/two_pointer.py)
* [Two Sum](https://github.com/TheAlgorithms/Python/blob/master/other/two_sum.py)
* [Word Patterns](https://github.com/TheAlgorithms/Python/blob/master/other/word_patterns.py)
## Project Euler
* Problem 001
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol3.py)
* [Sol4](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol4.py)
* [Sol5](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol5.py)
* [Sol6](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol6.py)
* [Sol7](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol7.py)
* Problem 002
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol3.py)
* [Sol4](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol4.py)
* [Sol5](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol5.py)
* Problem 003
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_003/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_003/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_003/sol3.py)
* Problem 004
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_004/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_004/sol2.py)
* Problem 005
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_005/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_005/sol2.py)
* Problem 006
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_006/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_006/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_006/sol3.py)
* [Sol4](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_006/sol4.py)
* Problem 007
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_007/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_007/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_007/sol3.py)
* Problem 008
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_008/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_008/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_008/sol3.py)
* Problem 009
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_009/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_009/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_009/sol3.py)
* Problem 010
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_010/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_010/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_010/sol3.py)
* Problem 011
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_011/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_011/sol2.py)
* Problem 012
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_012/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_012/sol2.py)
* Problem 013
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_013/sol1.py)
* Problem 014
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_014/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_014/sol2.py)
* Problem 015
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_015/sol1.py)
* Problem 016
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_016/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_016/sol2.py)
* Problem 017
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_017/sol1.py)
* Problem 018
* [Solution](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_018/solution.py)
* Problem 019
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_019/sol1.py)
* Problem 020
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_020/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_020/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_020/sol3.py)
* [Sol4](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_020/sol4.py)
* Problem 021
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_021/sol1.py)
* Problem 022
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_022/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_022/sol2.py)
* Problem 023
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_023/sol1.py)
* Problem 024
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_024/sol1.py)
* Problem 025
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_025/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_025/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_025/sol3.py)
* Problem 026
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_026/sol1.py)
* Problem 027
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_027/sol1.py)
* Problem 028
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_028/sol1.py)
* Problem 029
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_029/sol1.py)
* Problem 030
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_030/sol1.py)
* Problem 031
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_031/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_031/sol2.py)
* Problem 032
* [Sol32](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_032/sol32.py)
* Problem 033
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_033/sol1.py)
* Problem 034
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_034/sol1.py)
* Problem 035
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_035/sol1.py)
* Problem 036
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_036/sol1.py)
* Problem 037
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_037/sol1.py)
* Problem 038
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_038/sol1.py)
* Problem 039
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_039/sol1.py)
* Problem 040
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_040/sol1.py)
* Problem 041
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_041/sol1.py)
* Problem 042
* [Solution42](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_042/solution42.py)
* Problem 043
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_043/sol1.py)
* Problem 044
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_044/sol1.py)
* Problem 045
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_045/sol1.py)
* Problem 046
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_046/sol1.py)
* Problem 047
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_047/sol1.py)
* Problem 048
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_048/sol1.py)
* Problem 049
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_049/sol1.py)
* Problem 050
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_050/sol1.py)
* Problem 051
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_051/sol1.py)
* Problem 052
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_052/sol1.py)
* Problem 053
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_053/sol1.py)
* Problem 054
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_054/sol1.py)
* [Test Poker Hand](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_054/test_poker_hand.py)
* Problem 055
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_055/sol1.py)
* Problem 056
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_056/sol1.py)
* Problem 057
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_057/sol1.py)
* Problem 058
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_058/sol1.py)
* Problem 059
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_059/sol1.py)
* Problem 062
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_062/sol1.py)
* Problem 063
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_063/sol1.py)
* Problem 064
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_064/sol1.py)
* Problem 065
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_065/sol1.py)
* Problem 067
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_067/sol1.py)
* Problem 069
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_069/sol1.py)
* Problem 070
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_070/sol1.py)
* Problem 071
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_071/sol1.py)
* Problem 072
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_072/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_072/sol2.py)
* Problem 074
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_074/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_074/sol2.py)
* Problem 075
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_075/sol1.py)
* Problem 076
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_076/sol1.py)
* Problem 077
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_077/sol1.py)
* Problem 080
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_080/sol1.py)
* Problem 081
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_081/sol1.py)
* Problem 085
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_085/sol1.py)
* Problem 086
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_086/sol1.py)
* Problem 087
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_087/sol1.py)
* Problem 089
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_089/sol1.py)
* Problem 091
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_091/sol1.py)
* Problem 097
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_097/sol1.py)
* Problem 099
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_099/sol1.py)
* Problem 101
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_101/sol1.py)
* Problem 102
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_102/sol1.py)
* Problem 107
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_107/sol1.py)
* Problem 109
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_109/sol1.py)
* Problem 112
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_112/sol1.py)
* Problem 113
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_113/sol1.py)
* Problem 119
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_119/sol1.py)
* Problem 120
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_120/sol1.py)
* Problem 123
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_123/sol1.py)
* Problem 125
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_125/sol1.py)
* Problem 129
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_129/sol1.py)
* Problem 135
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_135/sol1.py)
* Problem 173
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_173/sol1.py)
* Problem 174
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_174/sol1.py)
* Problem 180
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_180/sol1.py)
* Problem 188
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_188/sol1.py)
* Problem 191
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_191/sol1.py)
* Problem 203
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_203/sol1.py)
* Problem 206
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_206/sol1.py)
* Problem 207
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_207/sol1.py)
* Problem 234
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_234/sol1.py)
* Problem 301
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_301/sol1.py)
* Problem 551
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_551/sol1.py)
## Quantum
* [Deutsch Jozsa](https://github.com/TheAlgorithms/Python/blob/master/quantum/deutsch_jozsa.py)
* [Half Adder](https://github.com/TheAlgorithms/Python/blob/master/quantum/half_adder.py)
* [Not Gate](https://github.com/TheAlgorithms/Python/blob/master/quantum/not_gate.py)
* [Quantum Entanglement](https://github.com/TheAlgorithms/Python/blob/master/quantum/quantum_entanglement.py)
* [Ripple Adder Classic](https://github.com/TheAlgorithms/Python/blob/master/quantum/ripple_adder_classic.py)
* [Single Qubit Measure](https://github.com/TheAlgorithms/Python/blob/master/quantum/single_qubit_measure.py)
## Scheduling
* [First Come First Served](https://github.com/TheAlgorithms/Python/blob/master/scheduling/first_come_first_served.py)
* [Round Robin](https://github.com/TheAlgorithms/Python/blob/master/scheduling/round_robin.py)
* [Shortest Job First](https://github.com/TheAlgorithms/Python/blob/master/scheduling/shortest_job_first.py)
## Searches
* [Binary Search](https://github.com/TheAlgorithms/Python/blob/master/searches/binary_search.py)
* [Double Linear Search](https://github.com/TheAlgorithms/Python/blob/master/searches/double_linear_search.py)
* [Double Linear Search Recursion](https://github.com/TheAlgorithms/Python/blob/master/searches/double_linear_search_recursion.py)
* [Fibonacci Search](https://github.com/TheAlgorithms/Python/blob/master/searches/fibonacci_search.py)
* [Hill Climbing](https://github.com/TheAlgorithms/Python/blob/master/searches/hill_climbing.py)
* [Interpolation Search](https://github.com/TheAlgorithms/Python/blob/master/searches/interpolation_search.py)
* [Jump Search](https://github.com/TheAlgorithms/Python/blob/master/searches/jump_search.py)
* [Linear Search](https://github.com/TheAlgorithms/Python/blob/master/searches/linear_search.py)
* [Quick Select](https://github.com/TheAlgorithms/Python/blob/master/searches/quick_select.py)
* [Sentinel Linear Search](https://github.com/TheAlgorithms/Python/blob/master/searches/sentinel_linear_search.py)
* [Simple Binary Search](https://github.com/TheAlgorithms/Python/blob/master/searches/simple_binary_search.py)
* [Simulated Annealing](https://github.com/TheAlgorithms/Python/blob/master/searches/simulated_annealing.py)
* [Tabu Search](https://github.com/TheAlgorithms/Python/blob/master/searches/tabu_search.py)
* [Ternary Search](https://github.com/TheAlgorithms/Python/blob/master/searches/ternary_search.py)
## Sorts
* [Bead Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bead_sort.py)
* [Bitonic Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bitonic_sort.py)
* [Bogo Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bogo_sort.py)
* [Bubble Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bubble_sort.py)
* [Bucket Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bucket_sort.py)
* [Cocktail Shaker Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/cocktail_shaker_sort.py)
* [Comb Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/comb_sort.py)
* [Counting Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/counting_sort.py)
* [Cycle Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/cycle_sort.py)
* [Double Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/double_sort.py)
* [External Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/external_sort.py)
* [Gnome Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/gnome_sort.py)
* [Heap Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/heap_sort.py)
* [Insertion Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/insertion_sort.py)
* [Intro Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/intro_sort.py)
* [Iterative Merge Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/iterative_merge_sort.py)
* [Merge Insertion Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/merge_insertion_sort.py)
* [Merge Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/merge_sort.py)
* [Natural Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/natural_sort.py)
* [Odd Even Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/odd_even_sort.py)
* [Odd Even Transposition Parallel](https://github.com/TheAlgorithms/Python/blob/master/sorts/odd_even_transposition_parallel.py)
* [Odd Even Transposition Single Threaded](https://github.com/TheAlgorithms/Python/blob/master/sorts/odd_even_transposition_single_threaded.py)
* [Pancake Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/pancake_sort.py)
* [Patience Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/patience_sort.py)
* [Pigeon Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/pigeon_sort.py)
* [Pigeonhole Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/pigeonhole_sort.py)
* [Quick Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/quick_sort.py)
* [Quick Sort 3 Partition](https://github.com/TheAlgorithms/Python/blob/master/sorts/quick_sort_3_partition.py)
* [Radix Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/radix_sort.py)
* [Random Normal Distribution Quicksort](https://github.com/TheAlgorithms/Python/blob/master/sorts/random_normal_distribution_quicksort.py)
* [Random Pivot Quick Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/random_pivot_quick_sort.py)
* [Recursive Bubble Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/recursive_bubble_sort.py)
* [Recursive Insertion Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/recursive_insertion_sort.py)
* [Recursive Quick Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/recursive_quick_sort.py)
* [Selection Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/selection_sort.py)
* [Shell Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/shell_sort.py)
* [Slowsort](https://github.com/TheAlgorithms/Python/blob/master/sorts/slowsort.py)
* [Stooge Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/stooge_sort.py)
* [Strand Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/strand_sort.py)
* [Tim Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/tim_sort.py)
* [Topological Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/topological_sort.py)
* [Tree Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/tree_sort.py)
* [Unknown Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/unknown_sort.py)
* [Wiggle Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/wiggle_sort.py)
## Strings
* [Aho Corasick](https://github.com/TheAlgorithms/Python/blob/master/strings/aho_corasick.py)
* [Boyer Moore Search](https://github.com/TheAlgorithms/Python/blob/master/strings/boyer_moore_search.py)
* [Can String Be Rearranged As Palindrome](https://github.com/TheAlgorithms/Python/blob/master/strings/can_string_be_rearranged_as_palindrome.py)
* [Capitalize](https://github.com/TheAlgorithms/Python/blob/master/strings/capitalize.py)
* [Check Anagrams](https://github.com/TheAlgorithms/Python/blob/master/strings/check_anagrams.py)
* [Check Pangram](https://github.com/TheAlgorithms/Python/blob/master/strings/check_pangram.py)
* [Is Palindrome](https://github.com/TheAlgorithms/Python/blob/master/strings/is_palindrome.py)
* [Jaro Winkler](https://github.com/TheAlgorithms/Python/blob/master/strings/jaro_winkler.py)
* [Knuth Morris Pratt](https://github.com/TheAlgorithms/Python/blob/master/strings/knuth_morris_pratt.py)
* [Levenshtein Distance](https://github.com/TheAlgorithms/Python/blob/master/strings/levenshtein_distance.py)
* [Lower](https://github.com/TheAlgorithms/Python/blob/master/strings/lower.py)
* [Manacher](https://github.com/TheAlgorithms/Python/blob/master/strings/manacher.py)
* [Min Cost String Conversion](https://github.com/TheAlgorithms/Python/blob/master/strings/min_cost_string_conversion.py)
* [Naive String Search](https://github.com/TheAlgorithms/Python/blob/master/strings/naive_string_search.py)
* [Prefix Function](https://github.com/TheAlgorithms/Python/blob/master/strings/prefix_function.py)
* [Rabin Karp](https://github.com/TheAlgorithms/Python/blob/master/strings/rabin_karp.py)
* [Remove Duplicate](https://github.com/TheAlgorithms/Python/blob/master/strings/remove_duplicate.py)
* [Reverse Letters](https://github.com/TheAlgorithms/Python/blob/master/strings/reverse_letters.py)
* [Reverse Words](https://github.com/TheAlgorithms/Python/blob/master/strings/reverse_words.py)
* [Split](https://github.com/TheAlgorithms/Python/blob/master/strings/split.py)
* [Swap Case](https://github.com/TheAlgorithms/Python/blob/master/strings/swap_case.py)
* [Upper](https://github.com/TheAlgorithms/Python/blob/master/strings/upper.py)
* [Word Occurrence](https://github.com/TheAlgorithms/Python/blob/master/strings/word_occurrence.py)
* [Z Function](https://github.com/TheAlgorithms/Python/blob/master/strings/z_function.py)
## Traversals
* [Binary Tree Traversals](https://github.com/TheAlgorithms/Python/blob/master/traversals/binary_tree_traversals.py)
## Web Programming
* [Co2 Emission](https://github.com/TheAlgorithms/Python/blob/master/web_programming/co2_emission.py)
* [Covid Stats Via Xpath](https://github.com/TheAlgorithms/Python/blob/master/web_programming/covid_stats_via_xpath.py)
* [Crawl Google Results](https://github.com/TheAlgorithms/Python/blob/master/web_programming/crawl_google_results.py)
* [Crawl Google Scholar Citation](https://github.com/TheAlgorithms/Python/blob/master/web_programming/crawl_google_scholar_citation.py)
* [Currency Converter](https://github.com/TheAlgorithms/Python/blob/master/web_programming/currency_converter.py)
* [Current Stock Price](https://github.com/TheAlgorithms/Python/blob/master/web_programming/current_stock_price.py)
* [Current Weather](https://github.com/TheAlgorithms/Python/blob/master/web_programming/current_weather.py)
* [Daily Horoscope](https://github.com/TheAlgorithms/Python/blob/master/web_programming/daily_horoscope.py)
* [Emails From Url](https://github.com/TheAlgorithms/Python/blob/master/web_programming/emails_from_url.py)
* [Fetch Bbc News](https://github.com/TheAlgorithms/Python/blob/master/web_programming/fetch_bbc_news.py)
* [Fetch Github Info](https://github.com/TheAlgorithms/Python/blob/master/web_programming/fetch_github_info.py)
* [Fetch Jobs](https://github.com/TheAlgorithms/Python/blob/master/web_programming/fetch_jobs.py)
* [Get Imdb Top 250 Movies Csv](https://github.com/TheAlgorithms/Python/blob/master/web_programming/get_imdb_top_250_movies_csv.py)
* [Get Imdbtop](https://github.com/TheAlgorithms/Python/blob/master/web_programming/get_imdbtop.py)
* [Instagram Crawler](https://github.com/TheAlgorithms/Python/blob/master/web_programming/instagram_crawler.py)
* [Instagram Pic](https://github.com/TheAlgorithms/Python/blob/master/web_programming/instagram_pic.py)
* [Instagram Video](https://github.com/TheAlgorithms/Python/blob/master/web_programming/instagram_video.py)
* [Recaptcha Verification](https://github.com/TheAlgorithms/Python/blob/master/web_programming/recaptcha_verification.py)
* [Slack Message](https://github.com/TheAlgorithms/Python/blob/master/web_programming/slack_message.py)
* [Test Fetch Github Info](https://github.com/TheAlgorithms/Python/blob/master/web_programming/test_fetch_github_info.py)
* [World Covid19 Stats](https://github.com/TheAlgorithms/Python/blob/master/web_programming/world_covid19_stats.py)
|
## Arithmetic Analysis
* [Bisection](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/bisection.py)
* [Gaussian Elimination](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/gaussian_elimination.py)
* [In Static Equilibrium](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/in_static_equilibrium.py)
* [Intersection](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/intersection.py)
* [Lu Decomposition](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/lu_decomposition.py)
* [Newton Forward Interpolation](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/newton_forward_interpolation.py)
* [Newton Method](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/newton_method.py)
* [Newton Raphson](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/newton_raphson.py)
* [Secant Method](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/secant_method.py)
## Backtracking
* [All Combinations](https://github.com/TheAlgorithms/Python/blob/master/backtracking/all_combinations.py)
* [All Permutations](https://github.com/TheAlgorithms/Python/blob/master/backtracking/all_permutations.py)
* [All Subsequences](https://github.com/TheAlgorithms/Python/blob/master/backtracking/all_subsequences.py)
* [Coloring](https://github.com/TheAlgorithms/Python/blob/master/backtracking/coloring.py)
* [Hamiltonian Cycle](https://github.com/TheAlgorithms/Python/blob/master/backtracking/hamiltonian_cycle.py)
* [Knight Tour](https://github.com/TheAlgorithms/Python/blob/master/backtracking/knight_tour.py)
* [Minimax](https://github.com/TheAlgorithms/Python/blob/master/backtracking/minimax.py)
* [N Queens](https://github.com/TheAlgorithms/Python/blob/master/backtracking/n_queens.py)
* [N Queens Math](https://github.com/TheAlgorithms/Python/blob/master/backtracking/n_queens_math.py)
* [Rat In Maze](https://github.com/TheAlgorithms/Python/blob/master/backtracking/rat_in_maze.py)
* [Sudoku](https://github.com/TheAlgorithms/Python/blob/master/backtracking/sudoku.py)
* [Sum Of Subsets](https://github.com/TheAlgorithms/Python/blob/master/backtracking/sum_of_subsets.py)
## Bit Manipulation
* [Binary And Operator](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_and_operator.py)
* [Binary Count Setbits](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_count_setbits.py)
* [Binary Count Trailing Zeros](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_count_trailing_zeros.py)
* [Binary Or Operator](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_or_operator.py)
* [Binary Shifts](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_shifts.py)
* [Binary Twos Complement](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_twos_complement.py)
* [Binary Xor Operator](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_xor_operator.py)
* [Count Number Of One Bits](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/count_number_of_one_bits.py)
* [Reverse Bits](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/reverse_bits.py)
* [Single Bit Manipulation Operations](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/single_bit_manipulation_operations.py)
## Blockchain
* [Chinese Remainder Theorem](https://github.com/TheAlgorithms/Python/blob/master/blockchain/chinese_remainder_theorem.py)
* [Diophantine Equation](https://github.com/TheAlgorithms/Python/blob/master/blockchain/diophantine_equation.py)
* [Modular Division](https://github.com/TheAlgorithms/Python/blob/master/blockchain/modular_division.py)
## Boolean Algebra
* [Quine Mc Cluskey](https://github.com/TheAlgorithms/Python/blob/master/boolean_algebra/quine_mc_cluskey.py)
## Cellular Automata
* [Conways Game Of Life](https://github.com/TheAlgorithms/Python/blob/master/cellular_automata/conways_game_of_life.py)
* [One Dimensional](https://github.com/TheAlgorithms/Python/blob/master/cellular_automata/one_dimensional.py)
## Ciphers
* [A1Z26](https://github.com/TheAlgorithms/Python/blob/master/ciphers/a1z26.py)
* [Affine Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/affine_cipher.py)
* [Atbash](https://github.com/TheAlgorithms/Python/blob/master/ciphers/atbash.py)
* [Base16](https://github.com/TheAlgorithms/Python/blob/master/ciphers/base16.py)
* [Base32](https://github.com/TheAlgorithms/Python/blob/master/ciphers/base32.py)
* [Base64 Encoding](https://github.com/TheAlgorithms/Python/blob/master/ciphers/base64_encoding.py)
* [Base85](https://github.com/TheAlgorithms/Python/blob/master/ciphers/base85.py)
* [Beaufort Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/beaufort_cipher.py)
* [Brute Force Caesar Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/brute_force_caesar_cipher.py)
* [Caesar Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/caesar_cipher.py)
* [Cryptomath Module](https://github.com/TheAlgorithms/Python/blob/master/ciphers/cryptomath_module.py)
* [Decrypt Caesar With Chi Squared](https://github.com/TheAlgorithms/Python/blob/master/ciphers/decrypt_caesar_with_chi_squared.py)
* [Deterministic Miller Rabin](https://github.com/TheAlgorithms/Python/blob/master/ciphers/deterministic_miller_rabin.py)
* [Diffie](https://github.com/TheAlgorithms/Python/blob/master/ciphers/diffie.py)
* [Diffie Hellman](https://github.com/TheAlgorithms/Python/blob/master/ciphers/diffie_hellman.py)
* [Elgamal Key Generator](https://github.com/TheAlgorithms/Python/blob/master/ciphers/elgamal_key_generator.py)
* [Enigma Machine2](https://github.com/TheAlgorithms/Python/blob/master/ciphers/enigma_machine2.py)
* [Hill Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/hill_cipher.py)
* [Mixed Keyword Cypher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/mixed_keyword_cypher.py)
* [Mono Alphabetic Ciphers](https://github.com/TheAlgorithms/Python/blob/master/ciphers/mono_alphabetic_ciphers.py)
* [Morse Code Implementation](https://github.com/TheAlgorithms/Python/blob/master/ciphers/morse_code_implementation.py)
* [Onepad Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/onepad_cipher.py)
* [Playfair Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/playfair_cipher.py)
* [Porta Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/porta_cipher.py)
* [Rabin Miller](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rabin_miller.py)
* [Rail Fence Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rail_fence_cipher.py)
* [Rot13](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rot13.py)
* [Rsa Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rsa_cipher.py)
* [Rsa Factorization](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rsa_factorization.py)
* [Rsa Key Generator](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rsa_key_generator.py)
* [Shuffled Shift Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/shuffled_shift_cipher.py)
* [Simple Keyword Cypher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/simple_keyword_cypher.py)
* [Simple Substitution Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/simple_substitution_cipher.py)
* [Trafid Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/trafid_cipher.py)
* [Transposition Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/transposition_cipher.py)
* [Transposition Cipher Encrypt Decrypt File](https://github.com/TheAlgorithms/Python/blob/master/ciphers/transposition_cipher_encrypt_decrypt_file.py)
* [Vigenere Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/vigenere_cipher.py)
* [Xor Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/xor_cipher.py)
## Compression
* [Burrows Wheeler](https://github.com/TheAlgorithms/Python/blob/master/compression/burrows_wheeler.py)
* [Huffman](https://github.com/TheAlgorithms/Python/blob/master/compression/huffman.py)
* [Lempel Ziv](https://github.com/TheAlgorithms/Python/blob/master/compression/lempel_ziv.py)
* [Lempel Ziv Decompress](https://github.com/TheAlgorithms/Python/blob/master/compression/lempel_ziv_decompress.py)
* [Peak Signal To Noise Ratio](https://github.com/TheAlgorithms/Python/blob/master/compression/peak_signal_to_noise_ratio.py)
## Computer Vision
* [Harriscorner](https://github.com/TheAlgorithms/Python/blob/master/computer_vision/harriscorner.py)
* [Meanthreshold](https://github.com/TheAlgorithms/Python/blob/master/computer_vision/meanthreshold.py)
## Conversions
* [Binary To Decimal](https://github.com/TheAlgorithms/Python/blob/master/conversions/binary_to_decimal.py)
* [Binary To Octal](https://github.com/TheAlgorithms/Python/blob/master/conversions/binary_to_octal.py)
* [Decimal To Any](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_any.py)
* [Decimal To Binary](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_binary.py)
* [Decimal To Binary Recursion](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_binary_recursion.py)
* [Decimal To Hexadecimal](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_hexadecimal.py)
* [Decimal To Octal](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_octal.py)
* [Hexadecimal To Decimal](https://github.com/TheAlgorithms/Python/blob/master/conversions/hexadecimal_to_decimal.py)
* [Molecular Chemistry](https://github.com/TheAlgorithms/Python/blob/master/conversions/molecular_chemistry.py)
* [Octal To Decimal](https://github.com/TheAlgorithms/Python/blob/master/conversions/octal_to_decimal.py)
* [Prefix Conversions](https://github.com/TheAlgorithms/Python/blob/master/conversions/prefix_conversions.py)
* [Roman Numerals](https://github.com/TheAlgorithms/Python/blob/master/conversions/roman_numerals.py)
* [Temperature Conversions](https://github.com/TheAlgorithms/Python/blob/master/conversions/temperature_conversions.py)
* [Weight Conversion](https://github.com/TheAlgorithms/Python/blob/master/conversions/weight_conversion.py)
## Data Structures
* Binary Tree
* [Avl Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/avl_tree.py)
* [Basic Binary Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/basic_binary_tree.py)
* [Binary Search Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/binary_search_tree.py)
* [Binary Search Tree Recursive](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/binary_search_tree_recursive.py)
* [Binary Tree Mirror](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/binary_tree_mirror.py)
* [Binary Tree Traversals](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/binary_tree_traversals.py)
* [Fenwick Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/fenwick_tree.py)
* [Lazy Segment Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/lazy_segment_tree.py)
* [Lowest Common Ancestor](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/lowest_common_ancestor.py)
* [Merge Two Binary Trees](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/merge_two_binary_trees.py)
* [Non Recursive Segment Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/non_recursive_segment_tree.py)
* [Number Of Possible Binary Trees](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/number_of_possible_binary_trees.py)
* [Red Black Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/red_black_tree.py)
* [Segment Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/segment_tree.py)
* [Segment Tree Other](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/segment_tree_other.py)
* [Treap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/treap.py)
* Disjoint Set
* [Alternate Disjoint Set](https://github.com/TheAlgorithms/Python/blob/master/data_structures/disjoint_set/alternate_disjoint_set.py)
* [Disjoint Set](https://github.com/TheAlgorithms/Python/blob/master/data_structures/disjoint_set/disjoint_set.py)
* Hashing
* [Double Hash](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/double_hash.py)
* [Hash Table](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/hash_table.py)
* [Hash Table With Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/hash_table_with_linked_list.py)
* Number Theory
* [Prime Numbers](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/number_theory/prime_numbers.py)
* [Quadratic Probing](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/quadratic_probing.py)
* Heap
* [Binomial Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/binomial_heap.py)
* [Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/heap.py)
* [Heap Generic](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/heap_generic.py)
* [Max Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/max_heap.py)
* [Min Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/min_heap.py)
* [Randomized Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/randomized_heap.py)
* [Skew Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/skew_heap.py)
* Linked List
* [Circular Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/circular_linked_list.py)
* [Deque Doubly](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/deque_doubly.py)
* [Doubly Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/doubly_linked_list.py)
* [Doubly Linked List Two](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/doubly_linked_list_two.py)
* [From Sequence](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/from_sequence.py)
* [Has Loop](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/has_loop.py)
* [Is Palindrome](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/is_palindrome.py)
* [Merge Two Lists](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/merge_two_lists.py)
* [Middle Element Of Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/middle_element_of_linked_list.py)
* [Print Reverse](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/print_reverse.py)
* [Singly Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/singly_linked_list.py)
* [Skip List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/skip_list.py)
* [Swap Nodes](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/swap_nodes.py)
* Queue
* [Circular Queue](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/circular_queue.py)
* [Double Ended Queue](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/double_ended_queue.py)
* [Linked Queue](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/linked_queue.py)
* [Priority Queue Using List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/priority_queue_using_list.py)
* [Queue On List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/queue_on_list.py)
* [Queue On Pseudo Stack](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/queue_on_pseudo_stack.py)
* Stacks
* [Balanced Parentheses](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/balanced_parentheses.py)
* [Dijkstras Two Stack Algorithm](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/dijkstras_two_stack_algorithm.py)
* [Evaluate Postfix Notations](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/evaluate_postfix_notations.py)
* [Infix To Postfix Conversion](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/infix_to_postfix_conversion.py)
* [Infix To Prefix Conversion](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/infix_to_prefix_conversion.py)
* [Linked Stack](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/linked_stack.py)
* [Next Greater Element](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/next_greater_element.py)
* [Postfix Evaluation](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/postfix_evaluation.py)
* [Prefix Evaluation](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/prefix_evaluation.py)
* [Stack](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/stack.py)
* [Stack Using Dll](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/stack_using_dll.py)
* [Stock Span Problem](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/stock_span_problem.py)
* Trie
* [Trie](https://github.com/TheAlgorithms/Python/blob/master/data_structures/trie/trie.py)
## Digital Image Processing
* [Change Brightness](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/change_brightness.py)
* [Change Contrast](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/change_contrast.py)
* [Convert To Negative](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/convert_to_negative.py)
* Dithering
* [Burkes](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/dithering/burkes.py)
* Edge Detection
* [Canny](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/edge_detection/canny.py)
* Filters
* [Bilateral Filter](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/bilateral_filter.py)
* [Convolve](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/convolve.py)
* [Gaussian Filter](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/gaussian_filter.py)
* [Median Filter](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/median_filter.py)
* [Sobel Filter](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/sobel_filter.py)
* Histogram Equalization
* [Histogram Stretch](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/histogram_equalization/histogram_stretch.py)
* [Index Calculation](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/index_calculation.py)
* Resize
* [Resize](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/resize/resize.py)
* Rotation
* [Rotation](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/rotation/rotation.py)
* [Sepia](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/sepia.py)
* [Test Digital Image Processing](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/test_digital_image_processing.py)
## Divide And Conquer
* [Closest Pair Of Points](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/closest_pair_of_points.py)
* [Convex Hull](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/convex_hull.py)
* [Heaps Algorithm](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/heaps_algorithm.py)
* [Heaps Algorithm Iterative](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/heaps_algorithm_iterative.py)
* [Inversions](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/inversions.py)
* [Kth Order Statistic](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/kth_order_statistic.py)
* [Max Difference Pair](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/max_difference_pair.py)
* [Max Subarray Sum](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/max_subarray_sum.py)
* [Mergesort](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/mergesort.py)
* [Peak](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/peak.py)
* [Power](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/power.py)
* [Strassen Matrix Multiplication](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/strassen_matrix_multiplication.py)
## Dynamic Programming
* [Abbreviation](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/abbreviation.py)
* [Bitmask](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/bitmask.py)
* [Climbing Stairs](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/climbing_stairs.py)
* [Edit Distance](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/edit_distance.py)
* [Factorial](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/factorial.py)
* [Fast Fibonacci](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/fast_fibonacci.py)
* [Fibonacci](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/fibonacci.py)
* [Floyd Warshall](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/floyd_warshall.py)
* [Fractional Knapsack](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/fractional_knapsack.py)
* [Fractional Knapsack 2](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/fractional_knapsack_2.py)
* [Integer Partition](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/integer_partition.py)
* [Iterating Through Submasks](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/iterating_through_submasks.py)
* [Knapsack](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/knapsack.py)
* [Longest Common Subsequence](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/longest_common_subsequence.py)
* [Longest Increasing Subsequence](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/longest_increasing_subsequence.py)
* [Longest Increasing Subsequence O(Nlogn)](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/longest_increasing_subsequence_o(nlogn).py)
* [Longest Sub Array](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/longest_sub_array.py)
* [Matrix Chain Order](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/matrix_chain_order.py)
* [Max Non Adjacent Sum](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/max_non_adjacent_sum.py)
* [Max Sub Array](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/max_sub_array.py)
* [Max Sum Contiguous Subsequence](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/max_sum_contiguous_subsequence.py)
* [Minimum Coin Change](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/minimum_coin_change.py)
* [Minimum Cost Path](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/minimum_cost_path.py)
* [Minimum Partition](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/minimum_partition.py)
* [Minimum Steps To One](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/minimum_steps_to_one.py)
* [Optimal Binary Search Tree](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/optimal_binary_search_tree.py)
* [Rod Cutting](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/rod_cutting.py)
* [Subset Generation](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/subset_generation.py)
* [Sum Of Subset](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/sum_of_subset.py)
## Electronics
* [Electric Power](https://github.com/TheAlgorithms/Python/blob/master/electronics/electric_power.py)
* [Ohms Law](https://github.com/TheAlgorithms/Python/blob/master/electronics/ohms_law.py)
## File Transfer
* [Receive File](https://github.com/TheAlgorithms/Python/blob/master/file_transfer/receive_file.py)
* [Send File](https://github.com/TheAlgorithms/Python/blob/master/file_transfer/send_file.py)
* Tests
* [Test Send File](https://github.com/TheAlgorithms/Python/blob/master/file_transfer/tests/test_send_file.py)
## Fuzzy Logic
* [Fuzzy Operations](https://github.com/TheAlgorithms/Python/blob/master/fuzzy_logic/fuzzy_operations.py)
## Genetic Algorithm
* [Basic String](https://github.com/TheAlgorithms/Python/blob/master/genetic_algorithm/basic_string.py)
## Geodesy
* [Haversine Distance](https://github.com/TheAlgorithms/Python/blob/master/geodesy/haversine_distance.py)
* [Lamberts Ellipsoidal Distance](https://github.com/TheAlgorithms/Python/blob/master/geodesy/lamberts_ellipsoidal_distance.py)
## Graphics
* [Bezier Curve](https://github.com/TheAlgorithms/Python/blob/master/graphics/bezier_curve.py)
* [Koch Snowflake](https://github.com/TheAlgorithms/Python/blob/master/graphics/koch_snowflake.py)
* [Mandelbrot](https://github.com/TheAlgorithms/Python/blob/master/graphics/mandelbrot.py)
* [Vector3 For 2D Rendering](https://github.com/TheAlgorithms/Python/blob/master/graphics/vector3_for_2d_rendering.py)
## Graphs
* [A Star](https://github.com/TheAlgorithms/Python/blob/master/graphs/a_star.py)
* [Articulation Points](https://github.com/TheAlgorithms/Python/blob/master/graphs/articulation_points.py)
* [Basic Graphs](https://github.com/TheAlgorithms/Python/blob/master/graphs/basic_graphs.py)
* [Bellman Ford](https://github.com/TheAlgorithms/Python/blob/master/graphs/bellman_ford.py)
* [Bfs Shortest Path](https://github.com/TheAlgorithms/Python/blob/master/graphs/bfs_shortest_path.py)
* [Bfs Zero One Shortest Path](https://github.com/TheAlgorithms/Python/blob/master/graphs/bfs_zero_one_shortest_path.py)
* [Bidirectional A Star](https://github.com/TheAlgorithms/Python/blob/master/graphs/bidirectional_a_star.py)
* [Bidirectional Breadth First Search](https://github.com/TheAlgorithms/Python/blob/master/graphs/bidirectional_breadth_first_search.py)
* [Breadth First Search](https://github.com/TheAlgorithms/Python/blob/master/graphs/breadth_first_search.py)
* [Breadth First Search 2](https://github.com/TheAlgorithms/Python/blob/master/graphs/breadth_first_search_2.py)
* [Breadth First Search Shortest Path](https://github.com/TheAlgorithms/Python/blob/master/graphs/breadth_first_search_shortest_path.py)
* [Check Bipartite Graph Bfs](https://github.com/TheAlgorithms/Python/blob/master/graphs/check_bipartite_graph_bfs.py)
* [Check Bipartite Graph Dfs](https://github.com/TheAlgorithms/Python/blob/master/graphs/check_bipartite_graph_dfs.py)
* [Connected Components](https://github.com/TheAlgorithms/Python/blob/master/graphs/connected_components.py)
* [Depth First Search](https://github.com/TheAlgorithms/Python/blob/master/graphs/depth_first_search.py)
* [Depth First Search 2](https://github.com/TheAlgorithms/Python/blob/master/graphs/depth_first_search_2.py)
* [Dijkstra](https://github.com/TheAlgorithms/Python/blob/master/graphs/dijkstra.py)
* [Dijkstra 2](https://github.com/TheAlgorithms/Python/blob/master/graphs/dijkstra_2.py)
* [Dijkstra Algorithm](https://github.com/TheAlgorithms/Python/blob/master/graphs/dijkstra_algorithm.py)
* [Dinic](https://github.com/TheAlgorithms/Python/blob/master/graphs/dinic.py)
* [Directed And Undirected (Weighted) Graph](https://github.com/TheAlgorithms/Python/blob/master/graphs/directed_and_undirected_(weighted)_graph.py)
* [Edmonds Karp Multiple Source And Sink](https://github.com/TheAlgorithms/Python/blob/master/graphs/edmonds_karp_multiple_source_and_sink.py)
* [Eulerian Path And Circuit For Undirected Graph](https://github.com/TheAlgorithms/Python/blob/master/graphs/eulerian_path_and_circuit_for_undirected_graph.py)
* [Even Tree](https://github.com/TheAlgorithms/Python/blob/master/graphs/even_tree.py)
* [Finding Bridges](https://github.com/TheAlgorithms/Python/blob/master/graphs/finding_bridges.py)
* [Frequent Pattern Graph Miner](https://github.com/TheAlgorithms/Python/blob/master/graphs/frequent_pattern_graph_miner.py)
* [G Topological Sort](https://github.com/TheAlgorithms/Python/blob/master/graphs/g_topological_sort.py)
* [Gale Shapley Bigraph](https://github.com/TheAlgorithms/Python/blob/master/graphs/gale_shapley_bigraph.py)
* [Graph List](https://github.com/TheAlgorithms/Python/blob/master/graphs/graph_list.py)
* [Graph Matrix](https://github.com/TheAlgorithms/Python/blob/master/graphs/graph_matrix.py)
* [Graphs Floyd Warshall](https://github.com/TheAlgorithms/Python/blob/master/graphs/graphs_floyd_warshall.py)
* [Greedy Best First](https://github.com/TheAlgorithms/Python/blob/master/graphs/greedy_best_first.py)
* [Kahns Algorithm Long](https://github.com/TheAlgorithms/Python/blob/master/graphs/kahns_algorithm_long.py)
* [Kahns Algorithm Topo](https://github.com/TheAlgorithms/Python/blob/master/graphs/kahns_algorithm_topo.py)
* [Karger](https://github.com/TheAlgorithms/Python/blob/master/graphs/karger.py)
* [Minimum Spanning Tree Boruvka](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_boruvka.py)
* [Minimum Spanning Tree Kruskal](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_kruskal.py)
* [Minimum Spanning Tree Kruskal2](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_kruskal2.py)
* [Minimum Spanning Tree Prims](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_prims.py)
* [Minimum Spanning Tree Prims2](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_prims2.py)
* [Multi Heuristic Astar](https://github.com/TheAlgorithms/Python/blob/master/graphs/multi_heuristic_astar.py)
* [Page Rank](https://github.com/TheAlgorithms/Python/blob/master/graphs/page_rank.py)
* [Prim](https://github.com/TheAlgorithms/Python/blob/master/graphs/prim.py)
* [Scc Kosaraju](https://github.com/TheAlgorithms/Python/blob/master/graphs/scc_kosaraju.py)
* [Strongly Connected Components](https://github.com/TheAlgorithms/Python/blob/master/graphs/strongly_connected_components.py)
* [Tarjans Scc](https://github.com/TheAlgorithms/Python/blob/master/graphs/tarjans_scc.py)
* Tests
* [Test Min Spanning Tree Kruskal](https://github.com/TheAlgorithms/Python/blob/master/graphs/tests/test_min_spanning_tree_kruskal.py)
* [Test Min Spanning Tree Prim](https://github.com/TheAlgorithms/Python/blob/master/graphs/tests/test_min_spanning_tree_prim.py)
## Hashes
* [Adler32](https://github.com/TheAlgorithms/Python/blob/master/hashes/adler32.py)
* [Chaos Machine](https://github.com/TheAlgorithms/Python/blob/master/hashes/chaos_machine.py)
* [Djb2](https://github.com/TheAlgorithms/Python/blob/master/hashes/djb2.py)
* [Enigma Machine](https://github.com/TheAlgorithms/Python/blob/master/hashes/enigma_machine.py)
* [Hamming Code](https://github.com/TheAlgorithms/Python/blob/master/hashes/hamming_code.py)
* [Md5](https://github.com/TheAlgorithms/Python/blob/master/hashes/md5.py)
* [Sdbm](https://github.com/TheAlgorithms/Python/blob/master/hashes/sdbm.py)
* [Sha1](https://github.com/TheAlgorithms/Python/blob/master/hashes/sha1.py)
## Knapsack
* [Greedy Knapsack](https://github.com/TheAlgorithms/Python/blob/master/knapsack/greedy_knapsack.py)
* [Knapsack](https://github.com/TheAlgorithms/Python/blob/master/knapsack/knapsack.py)
* Tests
* [Test Greedy Knapsack](https://github.com/TheAlgorithms/Python/blob/master/knapsack/tests/test_greedy_knapsack.py)
* [Test Knapsack](https://github.com/TheAlgorithms/Python/blob/master/knapsack/tests/test_knapsack.py)
## Linear Algebra
* Src
* [Conjugate Gradient](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/conjugate_gradient.py)
* [Lib](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/lib.py)
* [Polynom For Points](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/polynom_for_points.py)
* [Power Iteration](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/power_iteration.py)
* [Rayleigh Quotient](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/rayleigh_quotient.py)
* [Test Linear Algebra](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/test_linear_algebra.py)
* [Transformations 2D](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/transformations_2d.py)
## Machine Learning
* [Astar](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/astar.py)
* [Data Transformations](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/data_transformations.py)
* [Decision Tree](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/decision_tree.py)
* Forecasting
* [Run](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/forecasting/run.py)
* [Gaussian Naive Bayes](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gaussian_naive_bayes.py)
* [Gradient Boosting Regressor](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_boosting_regressor.py)
* [Gradient Descent](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_descent.py)
* [K Means Clust](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_means_clust.py)
* [K Nearest Neighbours](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_nearest_neighbours.py)
* [Knn Sklearn](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/knn_sklearn.py)
* [Linear Discriminant Analysis](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/linear_discriminant_analysis.py)
* [Linear Regression](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/linear_regression.py)
* [Logistic Regression](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/logistic_regression.py)
* [Multilayer Perceptron Classifier](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/multilayer_perceptron_classifier.py)
* [Polymonial Regression](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/polymonial_regression.py)
* [Random Forest Classifier](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/random_forest_classifier.py)
* [Random Forest Regressor](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/random_forest_regressor.py)
* [Scoring Functions](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/scoring_functions.py)
* [Sequential Minimum Optimization](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/sequential_minimum_optimization.py)
* [Similarity Search](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/similarity_search.py)
* [Support Vector Machines](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/support_vector_machines.py)
* [Word Frequency Functions](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/word_frequency_functions.py)
## Maths
* [3N Plus 1](https://github.com/TheAlgorithms/Python/blob/master/maths/3n_plus_1.py)
* [Abs](https://github.com/TheAlgorithms/Python/blob/master/maths/abs.py)
* [Abs Max](https://github.com/TheAlgorithms/Python/blob/master/maths/abs_max.py)
* [Abs Min](https://github.com/TheAlgorithms/Python/blob/master/maths/abs_min.py)
* [Add](https://github.com/TheAlgorithms/Python/blob/master/maths/add.py)
* [Aliquot Sum](https://github.com/TheAlgorithms/Python/blob/master/maths/aliquot_sum.py)
* [Allocation Number](https://github.com/TheAlgorithms/Python/blob/master/maths/allocation_number.py)
* [Area](https://github.com/TheAlgorithms/Python/blob/master/maths/area.py)
* [Area Under Curve](https://github.com/TheAlgorithms/Python/blob/master/maths/area_under_curve.py)
* [Armstrong Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/armstrong_numbers.py)
* [Average Mean](https://github.com/TheAlgorithms/Python/blob/master/maths/average_mean.py)
* [Average Median](https://github.com/TheAlgorithms/Python/blob/master/maths/average_median.py)
* [Average Mode](https://github.com/TheAlgorithms/Python/blob/master/maths/average_mode.py)
* [Bailey Borwein Plouffe](https://github.com/TheAlgorithms/Python/blob/master/maths/bailey_borwein_plouffe.py)
* [Basic Maths](https://github.com/TheAlgorithms/Python/blob/master/maths/basic_maths.py)
* [Binary Exp Mod](https://github.com/TheAlgorithms/Python/blob/master/maths/binary_exp_mod.py)
* [Binary Exponentiation](https://github.com/TheAlgorithms/Python/blob/master/maths/binary_exponentiation.py)
* [Binomial Coefficient](https://github.com/TheAlgorithms/Python/blob/master/maths/binomial_coefficient.py)
* [Binomial Distribution](https://github.com/TheAlgorithms/Python/blob/master/maths/binomial_distribution.py)
* [Bisection](https://github.com/TheAlgorithms/Python/blob/master/maths/bisection.py)
* [Ceil](https://github.com/TheAlgorithms/Python/blob/master/maths/ceil.py)
* [Chudnovsky Algorithm](https://github.com/TheAlgorithms/Python/blob/master/maths/chudnovsky_algorithm.py)
* [Collatz Sequence](https://github.com/TheAlgorithms/Python/blob/master/maths/collatz_sequence.py)
* [Combinations](https://github.com/TheAlgorithms/Python/blob/master/maths/combinations.py)
* [Decimal Isolate](https://github.com/TheAlgorithms/Python/blob/master/maths/decimal_isolate.py)
* [Entropy](https://github.com/TheAlgorithms/Python/blob/master/maths/entropy.py)
* [Euclidean Distance](https://github.com/TheAlgorithms/Python/blob/master/maths/euclidean_distance.py)
* [Eulers Totient](https://github.com/TheAlgorithms/Python/blob/master/maths/eulers_totient.py)
* [Explicit Euler](https://github.com/TheAlgorithms/Python/blob/master/maths/explicit_euler.py)
* [Extended Euclidean Algorithm](https://github.com/TheAlgorithms/Python/blob/master/maths/extended_euclidean_algorithm.py)
* [Factorial Iterative](https://github.com/TheAlgorithms/Python/blob/master/maths/factorial_iterative.py)
* [Factorial Python](https://github.com/TheAlgorithms/Python/blob/master/maths/factorial_python.py)
* [Factorial Recursive](https://github.com/TheAlgorithms/Python/blob/master/maths/factorial_recursive.py)
* [Factors](https://github.com/TheAlgorithms/Python/blob/master/maths/factors.py)
* [Fermat Little Theorem](https://github.com/TheAlgorithms/Python/blob/master/maths/fermat_little_theorem.py)
* [Fibonacci](https://github.com/TheAlgorithms/Python/blob/master/maths/fibonacci.py)
* [Fibonacci Sequence Recursion](https://github.com/TheAlgorithms/Python/blob/master/maths/fibonacci_sequence_recursion.py)
* [Find Max](https://github.com/TheAlgorithms/Python/blob/master/maths/find_max.py)
* [Find Max Recursion](https://github.com/TheAlgorithms/Python/blob/master/maths/find_max_recursion.py)
* [Find Min](https://github.com/TheAlgorithms/Python/blob/master/maths/find_min.py)
* [Find Min Recursion](https://github.com/TheAlgorithms/Python/blob/master/maths/find_min_recursion.py)
* [Floor](https://github.com/TheAlgorithms/Python/blob/master/maths/floor.py)
* [Gamma](https://github.com/TheAlgorithms/Python/blob/master/maths/gamma.py)
* [Gaussian](https://github.com/TheAlgorithms/Python/blob/master/maths/gaussian.py)
* [Greatest Common Divisor](https://github.com/TheAlgorithms/Python/blob/master/maths/greatest_common_divisor.py)
* [Hardy Ramanujanalgo](https://github.com/TheAlgorithms/Python/blob/master/maths/hardy_ramanujanalgo.py)
* [Is Square Free](https://github.com/TheAlgorithms/Python/blob/master/maths/is_square_free.py)
* [Jaccard Similarity](https://github.com/TheAlgorithms/Python/blob/master/maths/jaccard_similarity.py)
* [Kadanes](https://github.com/TheAlgorithms/Python/blob/master/maths/kadanes.py)
* [Karatsuba](https://github.com/TheAlgorithms/Python/blob/master/maths/karatsuba.py)
* [Krishnamurthy Number](https://github.com/TheAlgorithms/Python/blob/master/maths/krishnamurthy_number.py)
* [Kth Lexicographic Permutation](https://github.com/TheAlgorithms/Python/blob/master/maths/kth_lexicographic_permutation.py)
* [Largest Of Very Large Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/largest_of_very_large_numbers.py)
* [Least Common Multiple](https://github.com/TheAlgorithms/Python/blob/master/maths/least_common_multiple.py)
* [Line Length](https://github.com/TheAlgorithms/Python/blob/master/maths/line_length.py)
* [Lucas Lehmer Primality Test](https://github.com/TheAlgorithms/Python/blob/master/maths/lucas_lehmer_primality_test.py)
* [Lucas Series](https://github.com/TheAlgorithms/Python/blob/master/maths/lucas_series.py)
* [Matrix Exponentiation](https://github.com/TheAlgorithms/Python/blob/master/maths/matrix_exponentiation.py)
* [Miller Rabin](https://github.com/TheAlgorithms/Python/blob/master/maths/miller_rabin.py)
* [Mobius Function](https://github.com/TheAlgorithms/Python/blob/master/maths/mobius_function.py)
* [Modular Exponential](https://github.com/TheAlgorithms/Python/blob/master/maths/modular_exponential.py)
* [Monte Carlo](https://github.com/TheAlgorithms/Python/blob/master/maths/monte_carlo.py)
* [Monte Carlo Dice](https://github.com/TheAlgorithms/Python/blob/master/maths/monte_carlo_dice.py)
* [Newton Raphson](https://github.com/TheAlgorithms/Python/blob/master/maths/newton_raphson.py)
* [Number Of Digits](https://github.com/TheAlgorithms/Python/blob/master/maths/number_of_digits.py)
* [Numerical Integration](https://github.com/TheAlgorithms/Python/blob/master/maths/numerical_integration.py)
* [Perfect Cube](https://github.com/TheAlgorithms/Python/blob/master/maths/perfect_cube.py)
* [Perfect Number](https://github.com/TheAlgorithms/Python/blob/master/maths/perfect_number.py)
* [Perfect Square](https://github.com/TheAlgorithms/Python/blob/master/maths/perfect_square.py)
* [Pi Monte Carlo Estimation](https://github.com/TheAlgorithms/Python/blob/master/maths/pi_monte_carlo_estimation.py)
* [Polynomial Evaluation](https://github.com/TheAlgorithms/Python/blob/master/maths/polynomial_evaluation.py)
* [Power Using Recursion](https://github.com/TheAlgorithms/Python/blob/master/maths/power_using_recursion.py)
* [Prime Check](https://github.com/TheAlgorithms/Python/blob/master/maths/prime_check.py)
* [Prime Factors](https://github.com/TheAlgorithms/Python/blob/master/maths/prime_factors.py)
* [Prime Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/prime_numbers.py)
* [Prime Sieve Eratosthenes](https://github.com/TheAlgorithms/Python/blob/master/maths/prime_sieve_eratosthenes.py)
* [Pythagoras](https://github.com/TheAlgorithms/Python/blob/master/maths/pythagoras.py)
* [Qr Decomposition](https://github.com/TheAlgorithms/Python/blob/master/maths/qr_decomposition.py)
* [Quadratic Equations Complex Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/quadratic_equations_complex_numbers.py)
* [Radians](https://github.com/TheAlgorithms/Python/blob/master/maths/radians.py)
* [Radix2 Fft](https://github.com/TheAlgorithms/Python/blob/master/maths/radix2_fft.py)
* [Relu](https://github.com/TheAlgorithms/Python/blob/master/maths/relu.py)
* [Runge Kutta](https://github.com/TheAlgorithms/Python/blob/master/maths/runge_kutta.py)
* [Segmented Sieve](https://github.com/TheAlgorithms/Python/blob/master/maths/segmented_sieve.py)
* Series
* [Arithmetic Mean](https://github.com/TheAlgorithms/Python/blob/master/maths/series/arithmetic_mean.py)
* [Geometric Mean](https://github.com/TheAlgorithms/Python/blob/master/maths/series/geometric_mean.py)
* [Geometric Series](https://github.com/TheAlgorithms/Python/blob/master/maths/series/geometric_series.py)
* [Harmonic Series](https://github.com/TheAlgorithms/Python/blob/master/maths/series/harmonic_series.py)
* [P Series](https://github.com/TheAlgorithms/Python/blob/master/maths/series/p_series.py)
* [Sieve Of Eratosthenes](https://github.com/TheAlgorithms/Python/blob/master/maths/sieve_of_eratosthenes.py)
* [Sigmoid](https://github.com/TheAlgorithms/Python/blob/master/maths/sigmoid.py)
* [Simpson Rule](https://github.com/TheAlgorithms/Python/blob/master/maths/simpson_rule.py)
* [Softmax](https://github.com/TheAlgorithms/Python/blob/master/maths/softmax.py)
* [Square Root](https://github.com/TheAlgorithms/Python/blob/master/maths/square_root.py)
* [Sum Of Arithmetic Series](https://github.com/TheAlgorithms/Python/blob/master/maths/sum_of_arithmetic_series.py)
* [Sum Of Digits](https://github.com/TheAlgorithms/Python/blob/master/maths/sum_of_digits.py)
* [Sum Of Geometric Progression](https://github.com/TheAlgorithms/Python/blob/master/maths/sum_of_geometric_progression.py)
* [Test Prime Check](https://github.com/TheAlgorithms/Python/blob/master/maths/test_prime_check.py)
* [Trapezoidal Rule](https://github.com/TheAlgorithms/Python/blob/master/maths/trapezoidal_rule.py)
* [Ugly Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/ugly_numbers.py)
* [Volume](https://github.com/TheAlgorithms/Python/blob/master/maths/volume.py)
* [Zellers Congruence](https://github.com/TheAlgorithms/Python/blob/master/maths/zellers_congruence.py)
## Matrix
* [Count Islands In Matrix](https://github.com/TheAlgorithms/Python/blob/master/matrix/count_islands_in_matrix.py)
* [Inverse Of Matrix](https://github.com/TheAlgorithms/Python/blob/master/matrix/inverse_of_matrix.py)
* [Matrix Class](https://github.com/TheAlgorithms/Python/blob/master/matrix/matrix_class.py)
* [Matrix Operation](https://github.com/TheAlgorithms/Python/blob/master/matrix/matrix_operation.py)
* [Nth Fibonacci Using Matrix Exponentiation](https://github.com/TheAlgorithms/Python/blob/master/matrix/nth_fibonacci_using_matrix_exponentiation.py)
* [Rotate Matrix](https://github.com/TheAlgorithms/Python/blob/master/matrix/rotate_matrix.py)
* [Searching In Sorted Matrix](https://github.com/TheAlgorithms/Python/blob/master/matrix/searching_in_sorted_matrix.py)
* [Sherman Morrison](https://github.com/TheAlgorithms/Python/blob/master/matrix/sherman_morrison.py)
* [Spiral Print](https://github.com/TheAlgorithms/Python/blob/master/matrix/spiral_print.py)
* Tests
* [Test Matrix Operation](https://github.com/TheAlgorithms/Python/blob/master/matrix/tests/test_matrix_operation.py)
## Networking Flow
* [Ford Fulkerson](https://github.com/TheAlgorithms/Python/blob/master/networking_flow/ford_fulkerson.py)
* [Minimum Cut](https://github.com/TheAlgorithms/Python/blob/master/networking_flow/minimum_cut.py)
## Neural Network
* [2 Hidden Layers Neural Network](https://github.com/TheAlgorithms/Python/blob/master/neural_network/2_hidden_layers_neural_network.py)
* [Back Propagation Neural Network](https://github.com/TheAlgorithms/Python/blob/master/neural_network/back_propagation_neural_network.py)
* [Convolution Neural Network](https://github.com/TheAlgorithms/Python/blob/master/neural_network/convolution_neural_network.py)
* [Perceptron](https://github.com/TheAlgorithms/Python/blob/master/neural_network/perceptron.py)
## Other
* [Activity Selection](https://github.com/TheAlgorithms/Python/blob/master/other/activity_selection.py)
* [Anagrams](https://github.com/TheAlgorithms/Python/blob/master/other/anagrams.py)
* [Autocomplete Using Trie](https://github.com/TheAlgorithms/Python/blob/master/other/autocomplete_using_trie.py)
* [Binary Exponentiation](https://github.com/TheAlgorithms/Python/blob/master/other/binary_exponentiation.py)
* [Binary Exponentiation 2](https://github.com/TheAlgorithms/Python/blob/master/other/binary_exponentiation_2.py)
* [Davis–Putnam–Logemann–Loveland](https://github.com/TheAlgorithms/Python/blob/master/other/davis–putnam–logemann–loveland.py)
* [Detecting English Programmatically](https://github.com/TheAlgorithms/Python/blob/master/other/detecting_english_programmatically.py)
* [Dijkstra Bankers Algorithm](https://github.com/TheAlgorithms/Python/blob/master/other/dijkstra_bankers_algorithm.py)
* [Doomsday](https://github.com/TheAlgorithms/Python/blob/master/other/doomsday.py)
* [Euclidean Gcd](https://github.com/TheAlgorithms/Python/blob/master/other/euclidean_gcd.py)
* [Fischer Yates Shuffle](https://github.com/TheAlgorithms/Python/blob/master/other/fischer_yates_shuffle.py)
* [Frequency Finder](https://github.com/TheAlgorithms/Python/blob/master/other/frequency_finder.py)
* [Game Of Life](https://github.com/TheAlgorithms/Python/blob/master/other/game_of_life.py)
* [Gauss Easter](https://github.com/TheAlgorithms/Python/blob/master/other/gauss_easter.py)
* [Graham Scan](https://github.com/TheAlgorithms/Python/blob/master/other/graham_scan.py)
* [Greedy](https://github.com/TheAlgorithms/Python/blob/master/other/greedy.py)
* [Integeration By Simpson Approx](https://github.com/TheAlgorithms/Python/blob/master/other/integeration_by_simpson_approx.py)
* [Largest Subarray Sum](https://github.com/TheAlgorithms/Python/blob/master/other/largest_subarray_sum.py)
* [Least Recently Used](https://github.com/TheAlgorithms/Python/blob/master/other/least_recently_used.py)
* [Lfu Cache](https://github.com/TheAlgorithms/Python/blob/master/other/lfu_cache.py)
* [Linear Congruential Generator](https://github.com/TheAlgorithms/Python/blob/master/other/linear_congruential_generator.py)
* [Lru Cache](https://github.com/TheAlgorithms/Python/blob/master/other/lru_cache.py)
* [Magicdiamondpattern](https://github.com/TheAlgorithms/Python/blob/master/other/magicdiamondpattern.py)
* [Markov Chain](https://github.com/TheAlgorithms/Python/blob/master/other/markov_chain.py)
* [Max Sum Sliding Window](https://github.com/TheAlgorithms/Python/blob/master/other/max_sum_sliding_window.py)
* [Median Of Two Arrays](https://github.com/TheAlgorithms/Python/blob/master/other/median_of_two_arrays.py)
* [Nested Brackets](https://github.com/TheAlgorithms/Python/blob/master/other/nested_brackets.py)
* [Palindrome](https://github.com/TheAlgorithms/Python/blob/master/other/palindrome.py)
* [Password Generator](https://github.com/TheAlgorithms/Python/blob/master/other/password_generator.py)
* [Primelib](https://github.com/TheAlgorithms/Python/blob/master/other/primelib.py)
* [Scoring Algorithm](https://github.com/TheAlgorithms/Python/blob/master/other/scoring_algorithm.py)
* [Sdes](https://github.com/TheAlgorithms/Python/blob/master/other/sdes.py)
* [Sierpinski Triangle](https://github.com/TheAlgorithms/Python/blob/master/other/sierpinski_triangle.py)
* [Tower Of Hanoi](https://github.com/TheAlgorithms/Python/blob/master/other/tower_of_hanoi.py)
* [Triplet Sum](https://github.com/TheAlgorithms/Python/blob/master/other/triplet_sum.py)
* [Two Pointer](https://github.com/TheAlgorithms/Python/blob/master/other/two_pointer.py)
* [Two Sum](https://github.com/TheAlgorithms/Python/blob/master/other/two_sum.py)
* [Word Patterns](https://github.com/TheAlgorithms/Python/blob/master/other/word_patterns.py)
## Project Euler
* Problem 001
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol3.py)
* [Sol4](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol4.py)
* [Sol5](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol5.py)
* [Sol6](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol6.py)
* [Sol7](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol7.py)
* Problem 002
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol3.py)
* [Sol4](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol4.py)
* [Sol5](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol5.py)
* Problem 003
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_003/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_003/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_003/sol3.py)
* Problem 004
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_004/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_004/sol2.py)
* Problem 005
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_005/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_005/sol2.py)
* Problem 006
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_006/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_006/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_006/sol3.py)
* [Sol4](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_006/sol4.py)
* Problem 007
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_007/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_007/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_007/sol3.py)
* Problem 008
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_008/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_008/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_008/sol3.py)
* Problem 009
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_009/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_009/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_009/sol3.py)
* Problem 010
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_010/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_010/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_010/sol3.py)
* Problem 011
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_011/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_011/sol2.py)
* Problem 012
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_012/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_012/sol2.py)
* Problem 013
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_013/sol1.py)
* Problem 014
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_014/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_014/sol2.py)
* Problem 015
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_015/sol1.py)
* Problem 016
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_016/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_016/sol2.py)
* Problem 017
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_017/sol1.py)
* Problem 018
* [Solution](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_018/solution.py)
* Problem 019
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_019/sol1.py)
* Problem 020
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_020/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_020/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_020/sol3.py)
* [Sol4](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_020/sol4.py)
* Problem 021
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_021/sol1.py)
* Problem 022
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_022/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_022/sol2.py)
* Problem 023
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_023/sol1.py)
* Problem 024
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_024/sol1.py)
* Problem 025
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_025/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_025/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_025/sol3.py)
* Problem 026
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_026/sol1.py)
* Problem 027
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_027/sol1.py)
* Problem 028
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_028/sol1.py)
* Problem 029
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_029/sol1.py)
* Problem 030
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_030/sol1.py)
* Problem 031
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_031/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_031/sol2.py)
* Problem 032
* [Sol32](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_032/sol32.py)
* Problem 033
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_033/sol1.py)
* Problem 034
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_034/sol1.py)
* Problem 035
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_035/sol1.py)
* Problem 036
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_036/sol1.py)
* Problem 037
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_037/sol1.py)
* Problem 038
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_038/sol1.py)
* Problem 039
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_039/sol1.py)
* Problem 040
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_040/sol1.py)
* Problem 041
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_041/sol1.py)
* Problem 042
* [Solution42](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_042/solution42.py)
* Problem 043
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_043/sol1.py)
* Problem 044
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_044/sol1.py)
* Problem 045
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_045/sol1.py)
* Problem 046
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_046/sol1.py)
* Problem 047
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_047/sol1.py)
* Problem 048
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_048/sol1.py)
* Problem 049
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_049/sol1.py)
* Problem 050
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_050/sol1.py)
* Problem 051
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_051/sol1.py)
* Problem 052
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_052/sol1.py)
* Problem 053
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_053/sol1.py)
* Problem 054
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_054/sol1.py)
* [Test Poker Hand](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_054/test_poker_hand.py)
* Problem 055
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_055/sol1.py)
* Problem 056
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_056/sol1.py)
* Problem 057
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_057/sol1.py)
* Problem 058
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_058/sol1.py)
* Problem 059
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_059/sol1.py)
* Problem 062
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_062/sol1.py)
* Problem 063
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_063/sol1.py)
* Problem 064
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_064/sol1.py)
* Problem 065
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_065/sol1.py)
* Problem 067
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_067/sol1.py)
* Problem 069
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_069/sol1.py)
* Problem 070
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_070/sol1.py)
* Problem 071
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_071/sol1.py)
* Problem 072
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_072/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_072/sol2.py)
* Problem 074
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_074/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_074/sol2.py)
* Problem 075
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_075/sol1.py)
* Problem 076
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_076/sol1.py)
* Problem 077
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_077/sol1.py)
* Problem 080
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_080/sol1.py)
* Problem 081
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_081/sol1.py)
* Problem 085
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_085/sol1.py)
* Problem 086
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_086/sol1.py)
* Problem 087
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_087/sol1.py)
* Problem 089
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_089/sol1.py)
* Problem 091
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_091/sol1.py)
* Problem 097
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_097/sol1.py)
* Problem 099
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_099/sol1.py)
* Problem 101
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_101/sol1.py)
* Problem 102
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_102/sol1.py)
* Problem 107
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_107/sol1.py)
* Problem 109
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_109/sol1.py)
* Problem 112
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_112/sol1.py)
* Problem 113
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_113/sol1.py)
* Problem 119
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_119/sol1.py)
* Problem 120
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_120/sol1.py)
* Problem 123
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_123/sol1.py)
* Problem 125
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_125/sol1.py)
* Problem 129
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_129/sol1.py)
* Problem 135
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_135/sol1.py)
* Problem 173
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_173/sol1.py)
* Problem 174
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_174/sol1.py)
* Problem 180
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_180/sol1.py)
* Problem 188
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_188/sol1.py)
* Problem 191
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_191/sol1.py)
* Problem 203
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_203/sol1.py)
* Problem 206
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_206/sol1.py)
* Problem 207
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_207/sol1.py)
* Problem 234
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_234/sol1.py)
* Problem 301
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_301/sol1.py)
* Problem 551
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_551/sol1.py)
## Quantum
* [Deutsch Jozsa](https://github.com/TheAlgorithms/Python/blob/master/quantum/deutsch_jozsa.py)
* [Half Adder](https://github.com/TheAlgorithms/Python/blob/master/quantum/half_adder.py)
* [Not Gate](https://github.com/TheAlgorithms/Python/blob/master/quantum/not_gate.py)
* [Quantum Entanglement](https://github.com/TheAlgorithms/Python/blob/master/quantum/quantum_entanglement.py)
* [Ripple Adder Classic](https://github.com/TheAlgorithms/Python/blob/master/quantum/ripple_adder_classic.py)
* [Single Qubit Measure](https://github.com/TheAlgorithms/Python/blob/master/quantum/single_qubit_measure.py)
## Scheduling
* [First Come First Served](https://github.com/TheAlgorithms/Python/blob/master/scheduling/first_come_first_served.py)
* [Round Robin](https://github.com/TheAlgorithms/Python/blob/master/scheduling/round_robin.py)
* [Shortest Job First](https://github.com/TheAlgorithms/Python/blob/master/scheduling/shortest_job_first.py)
## Searches
* [Binary Search](https://github.com/TheAlgorithms/Python/blob/master/searches/binary_search.py)
* [Double Linear Search](https://github.com/TheAlgorithms/Python/blob/master/searches/double_linear_search.py)
* [Double Linear Search Recursion](https://github.com/TheAlgorithms/Python/blob/master/searches/double_linear_search_recursion.py)
* [Fibonacci Search](https://github.com/TheAlgorithms/Python/blob/master/searches/fibonacci_search.py)
* [Hill Climbing](https://github.com/TheAlgorithms/Python/blob/master/searches/hill_climbing.py)
* [Interpolation Search](https://github.com/TheAlgorithms/Python/blob/master/searches/interpolation_search.py)
* [Jump Search](https://github.com/TheAlgorithms/Python/blob/master/searches/jump_search.py)
* [Linear Search](https://github.com/TheAlgorithms/Python/blob/master/searches/linear_search.py)
* [Quick Select](https://github.com/TheAlgorithms/Python/blob/master/searches/quick_select.py)
* [Sentinel Linear Search](https://github.com/TheAlgorithms/Python/blob/master/searches/sentinel_linear_search.py)
* [Simple Binary Search](https://github.com/TheAlgorithms/Python/blob/master/searches/simple_binary_search.py)
* [Simulated Annealing](https://github.com/TheAlgorithms/Python/blob/master/searches/simulated_annealing.py)
* [Tabu Search](https://github.com/TheAlgorithms/Python/blob/master/searches/tabu_search.py)
* [Ternary Search](https://github.com/TheAlgorithms/Python/blob/master/searches/ternary_search.py)
## Sorts
* [Bead Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bead_sort.py)
* [Bitonic Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bitonic_sort.py)
* [Bogo Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bogo_sort.py)
* [Bubble Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bubble_sort.py)
* [Bucket Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bucket_sort.py)
* [Cocktail Shaker Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/cocktail_shaker_sort.py)
* [Comb Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/comb_sort.py)
* [Counting Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/counting_sort.py)
* [Cycle Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/cycle_sort.py)
* [Double Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/double_sort.py)
* [External Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/external_sort.py)
* [Gnome Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/gnome_sort.py)
* [Heap Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/heap_sort.py)
* [Insertion Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/insertion_sort.py)
* [Intro Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/intro_sort.py)
* [Iterative Merge Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/iterative_merge_sort.py)
* [Merge Insertion Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/merge_insertion_sort.py)
* [Merge Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/merge_sort.py)
* [Natural Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/natural_sort.py)
* [Odd Even Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/odd_even_sort.py)
* [Odd Even Transposition Parallel](https://github.com/TheAlgorithms/Python/blob/master/sorts/odd_even_transposition_parallel.py)
* [Odd Even Transposition Single Threaded](https://github.com/TheAlgorithms/Python/blob/master/sorts/odd_even_transposition_single_threaded.py)
* [Pancake Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/pancake_sort.py)
* [Patience Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/patience_sort.py)
* [Pigeon Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/pigeon_sort.py)
* [Pigeonhole Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/pigeonhole_sort.py)
* [Quick Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/quick_sort.py)
* [Quick Sort 3 Partition](https://github.com/TheAlgorithms/Python/blob/master/sorts/quick_sort_3_partition.py)
* [Radix Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/radix_sort.py)
* [Random Normal Distribution Quicksort](https://github.com/TheAlgorithms/Python/blob/master/sorts/random_normal_distribution_quicksort.py)
* [Random Pivot Quick Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/random_pivot_quick_sort.py)
* [Recursive Bubble Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/recursive_bubble_sort.py)
* [Recursive Insertion Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/recursive_insertion_sort.py)
* [Recursive Quick Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/recursive_quick_sort.py)
* [Selection Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/selection_sort.py)
* [Shell Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/shell_sort.py)
* [Slowsort](https://github.com/TheAlgorithms/Python/blob/master/sorts/slowsort.py)
* [Stooge Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/stooge_sort.py)
* [Strand Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/strand_sort.py)
* [Tim Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/tim_sort.py)
* [Topological Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/topological_sort.py)
* [Tree Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/tree_sort.py)
* [Unknown Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/unknown_sort.py)
* [Wiggle Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/wiggle_sort.py)
## Strings
* [Aho Corasick](https://github.com/TheAlgorithms/Python/blob/master/strings/aho_corasick.py)
* [Boyer Moore Search](https://github.com/TheAlgorithms/Python/blob/master/strings/boyer_moore_search.py)
* [Can String Be Rearranged As Palindrome](https://github.com/TheAlgorithms/Python/blob/master/strings/can_string_be_rearranged_as_palindrome.py)
* [Capitalize](https://github.com/TheAlgorithms/Python/blob/master/strings/capitalize.py)
* [Check Anagrams](https://github.com/TheAlgorithms/Python/blob/master/strings/check_anagrams.py)
* [Check Pangram](https://github.com/TheAlgorithms/Python/blob/master/strings/check_pangram.py)
* [Is Palindrome](https://github.com/TheAlgorithms/Python/blob/master/strings/is_palindrome.py)
* [Jaro Winkler](https://github.com/TheAlgorithms/Python/blob/master/strings/jaro_winkler.py)
* [Knuth Morris Pratt](https://github.com/TheAlgorithms/Python/blob/master/strings/knuth_morris_pratt.py)
* [Levenshtein Distance](https://github.com/TheAlgorithms/Python/blob/master/strings/levenshtein_distance.py)
* [Lower](https://github.com/TheAlgorithms/Python/blob/master/strings/lower.py)
* [Manacher](https://github.com/TheAlgorithms/Python/blob/master/strings/manacher.py)
* [Min Cost String Conversion](https://github.com/TheAlgorithms/Python/blob/master/strings/min_cost_string_conversion.py)
* [Naive String Search](https://github.com/TheAlgorithms/Python/blob/master/strings/naive_string_search.py)
* [Prefix Function](https://github.com/TheAlgorithms/Python/blob/master/strings/prefix_function.py)
* [Rabin Karp](https://github.com/TheAlgorithms/Python/blob/master/strings/rabin_karp.py)
* [Remove Duplicate](https://github.com/TheAlgorithms/Python/blob/master/strings/remove_duplicate.py)
* [Reverse Letters](https://github.com/TheAlgorithms/Python/blob/master/strings/reverse_letters.py)
* [Reverse Words](https://github.com/TheAlgorithms/Python/blob/master/strings/reverse_words.py)
* [Split](https://github.com/TheAlgorithms/Python/blob/master/strings/split.py)
* [Swap Case](https://github.com/TheAlgorithms/Python/blob/master/strings/swap_case.py)
* [Upper](https://github.com/TheAlgorithms/Python/blob/master/strings/upper.py)
* [Word Occurrence](https://github.com/TheAlgorithms/Python/blob/master/strings/word_occurrence.py)
* [Z Function](https://github.com/TheAlgorithms/Python/blob/master/strings/z_function.py)
## Traversals
* [Binary Tree Traversals](https://github.com/TheAlgorithms/Python/blob/master/traversals/binary_tree_traversals.py)
## Web Programming
* [Co2 Emission](https://github.com/TheAlgorithms/Python/blob/master/web_programming/co2_emission.py)
* [Covid Stats Via Xpath](https://github.com/TheAlgorithms/Python/blob/master/web_programming/covid_stats_via_xpath.py)
* [Crawl Google Results](https://github.com/TheAlgorithms/Python/blob/master/web_programming/crawl_google_results.py)
* [Crawl Google Scholar Citation](https://github.com/TheAlgorithms/Python/blob/master/web_programming/crawl_google_scholar_citation.py)
* [Currency Converter](https://github.com/TheAlgorithms/Python/blob/master/web_programming/currency_converter.py)
* [Current Stock Price](https://github.com/TheAlgorithms/Python/blob/master/web_programming/current_stock_price.py)
* [Current Weather](https://github.com/TheAlgorithms/Python/blob/master/web_programming/current_weather.py)
* [Daily Horoscope](https://github.com/TheAlgorithms/Python/blob/master/web_programming/daily_horoscope.py)
* [Emails From Url](https://github.com/TheAlgorithms/Python/blob/master/web_programming/emails_from_url.py)
* [Fetch Bbc News](https://github.com/TheAlgorithms/Python/blob/master/web_programming/fetch_bbc_news.py)
* [Fetch Github Info](https://github.com/TheAlgorithms/Python/blob/master/web_programming/fetch_github_info.py)
* [Fetch Jobs](https://github.com/TheAlgorithms/Python/blob/master/web_programming/fetch_jobs.py)
* [Get Imdb Top 250 Movies Csv](https://github.com/TheAlgorithms/Python/blob/master/web_programming/get_imdb_top_250_movies_csv.py)
* [Get Imdbtop](https://github.com/TheAlgorithms/Python/blob/master/web_programming/get_imdbtop.py)
* [Instagram Crawler](https://github.com/TheAlgorithms/Python/blob/master/web_programming/instagram_crawler.py)
* [Instagram Pic](https://github.com/TheAlgorithms/Python/blob/master/web_programming/instagram_pic.py)
* [Instagram Video](https://github.com/TheAlgorithms/Python/blob/master/web_programming/instagram_video.py)
* [Recaptcha Verification](https://github.com/TheAlgorithms/Python/blob/master/web_programming/recaptcha_verification.py)
* [Slack Message](https://github.com/TheAlgorithms/Python/blob/master/web_programming/slack_message.py)
* [Test Fetch Github Info](https://github.com/TheAlgorithms/Python/blob/master/web_programming/test_fetch_github_info.py)
* [World Covid19 Stats](https://github.com/TheAlgorithms/Python/blob/master/web_programming/world_covid19_stats.py)
| 1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
data = datasets.load_iris()
X = np.array(data["data"])
y = np.array(data["target"])
classes = data["target_names"]
X_train, X_test, y_train, y_test = train_test_split(X, y)
def euclidean_distance(a, b):
"""
Gives the euclidean distance between two points
>>> euclidean_distance([0, 0], [3, 4])
5.0
>>> euclidean_distance([1, 2, 3], [1, 8, 11])
10.0
"""
return np.linalg.norm(np.array(a) - np.array(b))
def classifier(train_data, train_target, classes, point, k=5):
"""
Classifies the point using the KNN algorithm
k closest points are found (ranked in ascending order of euclidean distance)
Params:
:train_data: Set of points that are classified into two or more classes
:train_target: List of classes in the order of train_data points
:classes: Labels of the classes
:point: The data point that needs to be classifed
>>> X_train = [[0, 0], [1, 0], [0, 1], [0.5, 0.5], [3, 3], [2, 3], [3, 2]]
>>> y_train = [0, 0, 0, 0, 1, 1, 1]
>>> classes = ['A','B']; point = [1.2,1.2]
>>> classifier(X_train, y_train, classes,point)
'A'
"""
data = zip(train_data, train_target)
# List of distances of all points from the point to be classified
distances = []
for data_point in data:
distance = euclidean_distance(data_point[0], point)
distances.append((distance, data_point[1]))
# Choosing 'k' points with the least distances.
votes = [i[1] for i in sorted(distances)[:k]]
# Most commonly occurring class among them
# is the class into which the point is classified
result = Counter(votes).most_common(1)[0][0]
return classes[result]
if __name__ == "__main__":
print(classifier(X_train, y_train, classes, [4.4, 3.1, 1.3, 1.4]))
| from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
data = datasets.load_iris()
X = np.array(data["data"])
y = np.array(data["target"])
classes = data["target_names"]
X_train, X_test, y_train, y_test = train_test_split(X, y)
def euclidean_distance(a, b):
"""
Gives the euclidean distance between two points
>>> euclidean_distance([0, 0], [3, 4])
5.0
>>> euclidean_distance([1, 2, 3], [1, 8, 11])
10.0
"""
return np.linalg.norm(np.array(a) - np.array(b))
def classifier(train_data, train_target, classes, point, k=5):
"""
Classifies the point using the KNN algorithm
k closest points are found (ranked in ascending order of euclidean distance)
Params:
:train_data: Set of points that are classified into two or more classes
:train_target: List of classes in the order of train_data points
:classes: Labels of the classes
:point: The data point that needs to be classified
>>> X_train = [[0, 0], [1, 0], [0, 1], [0.5, 0.5], [3, 3], [2, 3], [3, 2]]
>>> y_train = [0, 0, 0, 0, 1, 1, 1]
>>> classes = ['A','B']; point = [1.2,1.2]
>>> classifier(X_train, y_train, classes,point)
'A'
"""
data = zip(train_data, train_target)
# List of distances of all points from the point to be classified
distances = []
for data_point in data:
distance = euclidean_distance(data_point[0], point)
distances.append((distance, data_point[1]))
# Choosing 'k' points with the least distances.
votes = [i[1] for i in sorted(distances)[:k]]
# Most commonly occurring class among them
# is the class into which the point is classified
result = Counter(votes).most_common(1)[0][0]
return classes[result]
if __name__ == "__main__":
print(classifier(X_train, y_train, classes, [4.4, 3.1, 1.3, 1.4]))
| 1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from typing import Sequence
def evaluate_poly(poly: Sequence[float], x: float) -> float:
"""Evaluate a polynomial f(x) at specified point x and return the value.
Arguments:
poly -- the coeffiecients of a polynomial as an iterable in order of
ascending degree
x -- the point at which to evaluate the polynomial
>>> evaluate_poly((0.0, 0.0, 5.0, 9.3, 7.0), 10.0)
79800.0
"""
return sum(c * (x ** i) for i, c in enumerate(poly))
def horner(poly: Sequence[float], x: float) -> float:
"""Evaluate a polynomial at specified point using Horner's method.
In terms of computational complexity, Horner's method is an efficient method
of evaluating a polynomial. It avoids the use of expensive exponentiation,
and instead uses only multiplication and addition to evaluate the polynomial
in O(n), where n is the degree of the polynomial.
https://en.wikipedia.org/wiki/Horner's_method
Arguments:
poly -- the coeffiecients of a polynomial as an iterable in order of
ascending degree
x -- the point at which to evaluate the polynomial
>>> horner((0.0, 0.0, 5.0, 9.3, 7.0), 10.0)
79800.0
"""
result = 0.0
for coeff in reversed(poly):
result = result * x + coeff
return result
if __name__ == "__main__":
"""
Example:
>>> poly = (0.0, 0.0, 5.0, 9.3, 7.0) # f(x) = 7.0x^4 + 9.3x^3 + 5.0x^2
>>> x = -13.0
>>> # f(-13) = 7.0(-13)^4 + 9.3(-13)^3 + 5.0(-13)^2 = 180339.9
>>> print(evaluate_poly(poly, x))
180339.9
"""
poly = (0.0, 0.0, 5.0, 9.3, 7.0)
x = 10.0
print(evaluate_poly(poly, x))
print(horner(poly, x))
| from typing import Sequence
def evaluate_poly(poly: Sequence[float], x: float) -> float:
"""Evaluate a polynomial f(x) at specified point x and return the value.
Arguments:
poly -- the coefficients of a polynomial as an iterable in order of
ascending degree
x -- the point at which to evaluate the polynomial
>>> evaluate_poly((0.0, 0.0, 5.0, 9.3, 7.0), 10.0)
79800.0
"""
return sum(c * (x ** i) for i, c in enumerate(poly))
def horner(poly: Sequence[float], x: float) -> float:
"""Evaluate a polynomial at specified point using Horner's method.
In terms of computational complexity, Horner's method is an efficient method
of evaluating a polynomial. It avoids the use of expensive exponentiation,
and instead uses only multiplication and addition to evaluate the polynomial
in O(n), where n is the degree of the polynomial.
https://en.wikipedia.org/wiki/Horner's_method
Arguments:
poly -- the coefficients of a polynomial as an iterable in order of
ascending degree
x -- the point at which to evaluate the polynomial
>>> horner((0.0, 0.0, 5.0, 9.3, 7.0), 10.0)
79800.0
"""
result = 0.0
for coeff in reversed(poly):
result = result * x + coeff
return result
if __name__ == "__main__":
"""
Example:
>>> poly = (0.0, 0.0, 5.0, 9.3, 7.0) # f(x) = 7.0x^4 + 9.3x^3 + 5.0x^2
>>> x = -13.0
>>> # f(-13) = 7.0(-13)^4 + 9.3(-13)^3 + 5.0(-13)^2 = 180339.9
>>> print(evaluate_poly(poly, x))
180339.9
"""
poly = (0.0, 0.0, 5.0, 9.3, 7.0)
x = 10.0
print(evaluate_poly(poly, x))
print(horner(poly, x))
| 1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # https://en.wikipedia.org/wiki/Hill_climbing
import math
class SearchProblem:
"""
An interface to define search problems.
The interface will be illustrated using the example of mathematical function.
"""
def __init__(self, x: int, y: int, step_size: int, function_to_optimize):
"""
The constructor of the search problem.
x: the x coordinate of the current search state.
y: the y coordinate of the current search state.
step_size: size of the step to take when looking for neighbors.
function_to_optimize: a function to optimize having the signature f(x, y).
"""
self.x = x
self.y = y
self.step_size = step_size
self.function = function_to_optimize
def score(self) -> int:
"""
Returns the output of the function called with current x and y coordinates.
>>> def test_function(x, y):
... return x + y
>>> SearchProblem(0, 0, 1, test_function).score() # 0 + 0 = 0
0
>>> SearchProblem(5, 7, 1, test_function).score() # 5 + 7 = 12
12
"""
return self.function(self.x, self.y)
def get_neighbors(self):
"""
Returns a list of coordinates of neighbors adjacent to the current coordinates.
Neighbors:
| 0 | 1 | 2 |
| 3 | _ | 4 |
| 5 | 6 | 7 |
"""
step_size = self.step_size
return [
SearchProblem(x, y, step_size, self.function)
for x, y in (
(self.x - step_size, self.y - step_size),
(self.x - step_size, self.y),
(self.x - step_size, self.y + step_size),
(self.x, self.y - step_size),
(self.x, self.y + step_size),
(self.x + step_size, self.y - step_size),
(self.x + step_size, self.y),
(self.x + step_size, self.y + step_size),
)
]
def __hash__(self):
"""
hash the string represetation of the current search state.
"""
return hash(str(self))
def __eq__(self, obj):
"""
Check if the 2 objects are equal.
"""
if isinstance(obj, SearchProblem):
return hash(str(self)) == hash(str(obj))
return False
def __str__(self):
"""
string representation of the current search state.
>>> str(SearchProblem(0, 0, 1, None))
'x: 0 y: 0'
>>> str(SearchProblem(2, 5, 1, None))
'x: 2 y: 5'
"""
return f"x: {self.x} y: {self.y}"
def hill_climbing(
search_prob,
find_max: bool = True,
max_x: float = math.inf,
min_x: float = -math.inf,
max_y: float = math.inf,
min_y: float = -math.inf,
visualization: bool = False,
max_iter: int = 10000,
) -> SearchProblem:
"""
Implementation of the hill climbling algorithm.
We start with a given state, find all its neighbors,
move towards the neighbor which provides the maximum (or minimum) change.
We keep doing this until we are at a state where we do not have any
neighbors which can improve the solution.
Args:
search_prob: The search state at the start.
find_max: If True, the algorithm should find the maximum else the minimum.
max_x, min_x, max_y, min_y: the maximum and minimum bounds of x and y.
visualization: If True, a matplotlib graph is displayed.
max_iter: number of times to run the iteration.
Returns a search state having the maximum (or minimum) score.
"""
current_state = search_prob
scores = [] # list to store the current score at each iteration
iterations = 0
solution_found = False
visited = set()
while not solution_found and iterations < max_iter:
visited.add(current_state)
iterations += 1
current_score = current_state.score()
scores.append(current_score)
neighbors = current_state.get_neighbors()
max_change = -math.inf
min_change = math.inf
next_state = None # to hold the next best neighbor
for neighbor in neighbors:
if neighbor in visited:
continue # do not want to visit the same state again
if (
neighbor.x > max_x
or neighbor.x < min_x
or neighbor.y > max_y
or neighbor.y < min_y
):
continue # neighbor outside our bounds
change = neighbor.score() - current_score
if find_max: # finding max
# going to direction with greatest ascent
if change > max_change and change > 0:
max_change = change
next_state = neighbor
else: # finding min
# to direction with greatest descent
if change < min_change and change < 0:
min_change = change
next_state = neighbor
if next_state is not None:
# we found at least one neighbor which improved the current state
current_state = next_state
else:
# since we have no neighbor that improves the solution we stop the search
solution_found = True
if visualization:
from matplotlib import pyplot as plt
plt.plot(range(iterations), scores)
plt.xlabel("Iterations")
plt.ylabel("Function values")
plt.show()
return current_state
if __name__ == "__main__":
import doctest
doctest.testmod()
def test_f1(x, y):
return (x ** 2) + (y ** 2)
# starting the problem with initial coordinates (3, 4)
prob = SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_f1)
local_min = hill_climbing(prob, find_max=False)
print(
"The minimum score for f(x, y) = x^2 + y^2 found via hill climbing: "
f"{local_min.score()}"
)
# starting the problem with initial coordinates (12, 47)
prob = SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_f1)
local_min = hill_climbing(
prob, find_max=False, max_x=100, min_x=5, max_y=50, min_y=-5, visualization=True
)
print(
"The minimum score for f(x, y) = x^2 + y^2 with the domain 100 > x > 5 "
f"and 50 > y > - 5 found via hill climbing: {local_min.score()}"
)
def test_f2(x, y):
return (3 * x ** 2) - (6 * y)
prob = SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_f1)
local_min = hill_climbing(prob, find_max=True)
print(
"The maximum score for f(x, y) = x^2 + y^2 found via hill climbing: "
f"{local_min.score()}"
)
| # https://en.wikipedia.org/wiki/Hill_climbing
import math
class SearchProblem:
"""
An interface to define search problems.
The interface will be illustrated using the example of mathematical function.
"""
def __init__(self, x: int, y: int, step_size: int, function_to_optimize):
"""
The constructor of the search problem.
x: the x coordinate of the current search state.
y: the y coordinate of the current search state.
step_size: size of the step to take when looking for neighbors.
function_to_optimize: a function to optimize having the signature f(x, y).
"""
self.x = x
self.y = y
self.step_size = step_size
self.function = function_to_optimize
def score(self) -> int:
"""
Returns the output of the function called with current x and y coordinates.
>>> def test_function(x, y):
... return x + y
>>> SearchProblem(0, 0, 1, test_function).score() # 0 + 0 = 0
0
>>> SearchProblem(5, 7, 1, test_function).score() # 5 + 7 = 12
12
"""
return self.function(self.x, self.y)
def get_neighbors(self):
"""
Returns a list of coordinates of neighbors adjacent to the current coordinates.
Neighbors:
| 0 | 1 | 2 |
| 3 | _ | 4 |
| 5 | 6 | 7 |
"""
step_size = self.step_size
return [
SearchProblem(x, y, step_size, self.function)
for x, y in (
(self.x - step_size, self.y - step_size),
(self.x - step_size, self.y),
(self.x - step_size, self.y + step_size),
(self.x, self.y - step_size),
(self.x, self.y + step_size),
(self.x + step_size, self.y - step_size),
(self.x + step_size, self.y),
(self.x + step_size, self.y + step_size),
)
]
def __hash__(self):
"""
hash the string representation of the current search state.
"""
return hash(str(self))
def __eq__(self, obj):
"""
Check if the 2 objects are equal.
"""
if isinstance(obj, SearchProblem):
return hash(str(self)) == hash(str(obj))
return False
def __str__(self):
"""
string representation of the current search state.
>>> str(SearchProblem(0, 0, 1, None))
'x: 0 y: 0'
>>> str(SearchProblem(2, 5, 1, None))
'x: 2 y: 5'
"""
return f"x: {self.x} y: {self.y}"
def hill_climbing(
search_prob,
find_max: bool = True,
max_x: float = math.inf,
min_x: float = -math.inf,
max_y: float = math.inf,
min_y: float = -math.inf,
visualization: bool = False,
max_iter: int = 10000,
) -> SearchProblem:
"""
Implementation of the hill climbling algorithm.
We start with a given state, find all its neighbors,
move towards the neighbor which provides the maximum (or minimum) change.
We keep doing this until we are at a state where we do not have any
neighbors which can improve the solution.
Args:
search_prob: The search state at the start.
find_max: If True, the algorithm should find the maximum else the minimum.
max_x, min_x, max_y, min_y: the maximum and minimum bounds of x and y.
visualization: If True, a matplotlib graph is displayed.
max_iter: number of times to run the iteration.
Returns a search state having the maximum (or minimum) score.
"""
current_state = search_prob
scores = [] # list to store the current score at each iteration
iterations = 0
solution_found = False
visited = set()
while not solution_found and iterations < max_iter:
visited.add(current_state)
iterations += 1
current_score = current_state.score()
scores.append(current_score)
neighbors = current_state.get_neighbors()
max_change = -math.inf
min_change = math.inf
next_state = None # to hold the next best neighbor
for neighbor in neighbors:
if neighbor in visited:
continue # do not want to visit the same state again
if (
neighbor.x > max_x
or neighbor.x < min_x
or neighbor.y > max_y
or neighbor.y < min_y
):
continue # neighbor outside our bounds
change = neighbor.score() - current_score
if find_max: # finding max
# going to direction with greatest ascent
if change > max_change and change > 0:
max_change = change
next_state = neighbor
else: # finding min
# to direction with greatest descent
if change < min_change and change < 0:
min_change = change
next_state = neighbor
if next_state is not None:
# we found at least one neighbor which improved the current state
current_state = next_state
else:
# since we have no neighbor that improves the solution we stop the search
solution_found = True
if visualization:
from matplotlib import pyplot as plt
plt.plot(range(iterations), scores)
plt.xlabel("Iterations")
plt.ylabel("Function values")
plt.show()
return current_state
if __name__ == "__main__":
import doctest
doctest.testmod()
def test_f1(x, y):
return (x ** 2) + (y ** 2)
# starting the problem with initial coordinates (3, 4)
prob = SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_f1)
local_min = hill_climbing(prob, find_max=False)
print(
"The minimum score for f(x, y) = x^2 + y^2 found via hill climbing: "
f"{local_min.score()}"
)
# starting the problem with initial coordinates (12, 47)
prob = SearchProblem(x=12, y=47, step_size=1, function_to_optimize=test_f1)
local_min = hill_climbing(
prob, find_max=False, max_x=100, min_x=5, max_y=50, min_y=-5, visualization=True
)
print(
"The minimum score for f(x, y) = x^2 + y^2 with the domain 100 > x > 5 "
f"and 50 > y > - 5 found via hill climbing: {local_min.score()}"
)
def test_f2(x, y):
return (3 * x ** 2) - (6 * y)
prob = SearchProblem(x=3, y=4, step_size=1, function_to_optimize=test_f1)
local_min = hill_climbing(prob, find_max=True)
print(
"The maximum score for f(x, y) = x^2 + y^2 found via hill climbing: "
f"{local_min.score()}"
)
| 1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Isolate the Decimal part of a Number
https://stackoverflow.com/questions/3886402/how-to-get-numbers-after-decimal-point
"""
def decimal_isolate(number, digitAmount):
"""
Isolates the decimal part of a number.
If digitAmount > 0 round to that decimal place, else print the entire decimal.
>>> decimal_isolate(1.53, 0)
0.53
>>> decimal_isolate(35.345, 1)
0.3
>>> decimal_isolate(35.345, 2)
0.34
>>> decimal_isolate(35.345, 3)
0.345
>>> decimal_isolate(-14.789, 3)
-0.789
>>> decimal_isolate(0, 2)
0
>>> decimal_isolate(-14.123, 1)
-0.1
>>> decimal_isolate(-14.123, 2)
-0.12
>>> decimal_isolate(-14.123, 3)
-0.123
"""
if digitAmount > 0:
return round(number - int(number), digitAmount)
return number - int(number)
if __name__ == "__main__":
print(decimal_isolate(1.53, 0))
print(decimal_isolate(35.345, 1))
print(decimal_isolate(35.345, 2))
print(decimal_isolate(35.345, 3))
print(decimal_isolate(-14.789, 3))
print(decimal_isolate(0, 2))
print(decimal_isolate(-14.123, 1))
print(decimal_isolate(-14.123, 2))
print(decimal_isolate(-14.123, 3))
| """
Isolate the Decimal part of a Number
https://stackoverflow.com/questions/3886402/how-to-get-numbers-after-decimal-point
"""
def decimal_isolate(number, digitAmount):
"""
Isolates the decimal part of a number.
If digitAmount > 0 round to that decimal place, else print the entire decimal.
>>> decimal_isolate(1.53, 0)
0.53
>>> decimal_isolate(35.345, 1)
0.3
>>> decimal_isolate(35.345, 2)
0.34
>>> decimal_isolate(35.345, 3)
0.345
>>> decimal_isolate(-14.789, 3)
-0.789
>>> decimal_isolate(0, 2)
0
>>> decimal_isolate(-14.123, 1)
-0.1
>>> decimal_isolate(-14.123, 2)
-0.12
>>> decimal_isolate(-14.123, 3)
-0.123
"""
if digitAmount > 0:
return round(number - int(number), digitAmount)
return number - int(number)
if __name__ == "__main__":
print(decimal_isolate(1.53, 0))
print(decimal_isolate(35.345, 1))
print(decimal_isolate(35.345, 2))
print(decimal_isolate(35.345, 3))
print(decimal_isolate(-14.789, 3))
print(decimal_isolate(0, 2))
print(decimal_isolate(-14.123, 1))
print(decimal_isolate(-14.123, 2))
print(decimal_isolate(-14.123, 3))
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
disjoint set
Reference: https://en.wikipedia.org/wiki/Disjoint-set_data_structure
"""
class Node:
def __init__(self, data):
self.data = data
def make_set(x):
"""
make x as a set.
"""
# rank is the distance from x to its' parent
# root's rank is 0
x.rank = 0
x.parent = x
def union_set(x, y):
"""
union two sets.
set with bigger rank should be parent, so that the
disjoint set tree will be more flat.
"""
x, y = find_set(x), find_set(y)
if x.rank > y.rank:
y.parent = x
else:
x.parent = y
if x.rank == y.rank:
y.rank += 1
def find_set(x):
"""
return the parent of x
"""
if x != x.parent:
x.parent = find_set(x.parent)
return x.parent
def find_python_set(node: Node) -> set:
"""
Return a Python Standard Library set that contains i.
"""
sets = ({0, 1, 2}, {3, 4, 5})
for s in sets:
if node.data in s:
return s
raise ValueError(f"{node.data} is not in {sets}")
def test_disjoint_set():
"""
>>> test_disjoint_set()
"""
vertex = [Node(i) for i in range(6)]
for v in vertex:
make_set(v)
union_set(vertex[0], vertex[1])
union_set(vertex[1], vertex[2])
union_set(vertex[3], vertex[4])
union_set(vertex[3], vertex[5])
for node0 in vertex:
for node1 in vertex:
if find_python_set(node0).isdisjoint(find_python_set(node1)):
assert find_set(node0) != find_set(node1)
else:
assert find_set(node0) == find_set(node1)
if __name__ == "__main__":
test_disjoint_set()
| """
disjoint set
Reference: https://en.wikipedia.org/wiki/Disjoint-set_data_structure
"""
class Node:
def __init__(self, data):
self.data = data
def make_set(x):
"""
make x as a set.
"""
# rank is the distance from x to its' parent
# root's rank is 0
x.rank = 0
x.parent = x
def union_set(x, y):
"""
union two sets.
set with bigger rank should be parent, so that the
disjoint set tree will be more flat.
"""
x, y = find_set(x), find_set(y)
if x.rank > y.rank:
y.parent = x
else:
x.parent = y
if x.rank == y.rank:
y.rank += 1
def find_set(x):
"""
return the parent of x
"""
if x != x.parent:
x.parent = find_set(x.parent)
return x.parent
def find_python_set(node: Node) -> set:
"""
Return a Python Standard Library set that contains i.
"""
sets = ({0, 1, 2}, {3, 4, 5})
for s in sets:
if node.data in s:
return s
raise ValueError(f"{node.data} is not in {sets}")
def test_disjoint_set():
"""
>>> test_disjoint_set()
"""
vertex = [Node(i) for i in range(6)]
for v in vertex:
make_set(v)
union_set(vertex[0], vertex[1])
union_set(vertex[1], vertex[2])
union_set(vertex[3], vertex[4])
union_set(vertex[3], vertex[5])
for node0 in vertex:
for node1 in vertex:
if find_python_set(node0).isdisjoint(find_python_set(node1)):
assert find_set(node0) != find_set(node1)
else:
assert find_set(node0) == find_set(node1)
if __name__ == "__main__":
test_disjoint_set()
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Gaussian elimination method for solving a system of linear equations.
Gaussian elimination - https://en.wikipedia.org/wiki/Gaussian_elimination
"""
import numpy as np
def retroactive_resolution(coefficients: np.matrix, vector: np.array) -> np.array:
"""
This function performs a retroactive linear system resolution
for triangular matrix
Examples:
2x1 + 2x2 - 1x3 = 5 2x1 + 2x2 = -1
0x1 - 2x2 - 1x3 = -7 0x1 - 2x2 = -1
0x1 + 0x2 + 5x3 = 15
>>> gaussian_elimination([[2, 2, -1], [0, -2, -1], [0, 0, 5]], [[5], [-7], [15]])
array([[2.],
[2.],
[3.]])
>>> gaussian_elimination([[2, 2], [0, -2]], [[-1], [-1]])
array([[-1. ],
[ 0.5]])
"""
rows, columns = np.shape(coefficients)
x = np.zeros((rows, 1), dtype=float)
for row in reversed(range(rows)):
sum = 0
for col in range(row + 1, columns):
sum += coefficients[row, col] * x[col]
x[row, 0] = (vector[row] - sum) / coefficients[row, row]
return x
def gaussian_elimination(coefficients: np.matrix, vector: np.array) -> np.array:
"""
This function performs Gaussian elimination method
Examples:
1x1 - 4x2 - 2x3 = -2 1x1 + 2x2 = 5
5x1 + 2x2 - 2x3 = -3 5x1 + 2x2 = 5
1x1 - 1x2 + 0x3 = 4
>>> gaussian_elimination([[1, -4, -2], [5, 2, -2], [1, -1, 0]], [[-2], [-3], [4]])
array([[ 2.3 ],
[-1.7 ],
[ 5.55]])
>>> gaussian_elimination([[1, 2], [5, 2]], [[5], [5]])
array([[0. ],
[2.5]])
"""
# coefficients must to be a square matrix so we need to check first
rows, columns = np.shape(coefficients)
if rows != columns:
return []
# augmented matrix
augmented_mat = np.concatenate((coefficients, vector), axis=1)
augmented_mat = augmented_mat.astype("float64")
# scale the matrix leaving it triangular
for row in range(rows - 1):
pivot = augmented_mat[row, row]
for col in range(row + 1, columns):
factor = augmented_mat[col, row] / pivot
augmented_mat[col, :] -= factor * augmented_mat[row, :]
x = retroactive_resolution(
augmented_mat[:, 0:columns], augmented_mat[:, columns : columns + 1]
)
return x
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
Gaussian elimination method for solving a system of linear equations.
Gaussian elimination - https://en.wikipedia.org/wiki/Gaussian_elimination
"""
import numpy as np
def retroactive_resolution(coefficients: np.matrix, vector: np.array) -> np.array:
"""
This function performs a retroactive linear system resolution
for triangular matrix
Examples:
2x1 + 2x2 - 1x3 = 5 2x1 + 2x2 = -1
0x1 - 2x2 - 1x3 = -7 0x1 - 2x2 = -1
0x1 + 0x2 + 5x3 = 15
>>> gaussian_elimination([[2, 2, -1], [0, -2, -1], [0, 0, 5]], [[5], [-7], [15]])
array([[2.],
[2.],
[3.]])
>>> gaussian_elimination([[2, 2], [0, -2]], [[-1], [-1]])
array([[-1. ],
[ 0.5]])
"""
rows, columns = np.shape(coefficients)
x = np.zeros((rows, 1), dtype=float)
for row in reversed(range(rows)):
sum = 0
for col in range(row + 1, columns):
sum += coefficients[row, col] * x[col]
x[row, 0] = (vector[row] - sum) / coefficients[row, row]
return x
def gaussian_elimination(coefficients: np.matrix, vector: np.array) -> np.array:
"""
This function performs Gaussian elimination method
Examples:
1x1 - 4x2 - 2x3 = -2 1x1 + 2x2 = 5
5x1 + 2x2 - 2x3 = -3 5x1 + 2x2 = 5
1x1 - 1x2 + 0x3 = 4
>>> gaussian_elimination([[1, -4, -2], [5, 2, -2], [1, -1, 0]], [[-2], [-3], [4]])
array([[ 2.3 ],
[-1.7 ],
[ 5.55]])
>>> gaussian_elimination([[1, 2], [5, 2]], [[5], [5]])
array([[0. ],
[2.5]])
"""
# coefficients must to be a square matrix so we need to check first
rows, columns = np.shape(coefficients)
if rows != columns:
return []
# augmented matrix
augmented_mat = np.concatenate((coefficients, vector), axis=1)
augmented_mat = augmented_mat.astype("float64")
# scale the matrix leaving it triangular
for row in range(rows - 1):
pivot = augmented_mat[row, row]
for col in range(row + 1, columns):
factor = augmented_mat[col, row] / pivot
augmented_mat[col, :] -= factor * augmented_mat[row, :]
x = retroactive_resolution(
augmented_mat[:, 0:columns], augmented_mat[:, columns : columns + 1]
)
return x
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
https://cp-algorithms.com/string/prefix-function.html
Prefix function Knuth–Morris–Pratt algorithm
Different algorithm than Knuth-Morris-Pratt pattern finding
E.x. Finding longest prefix which is also suffix
Time Complexity: O(n) - where n is the length of the string
"""
def prefix_function(input_string: str) -> list:
"""
For the given string this function computes value for each index(i),
which represents the longest coincidence of prefix and sufix
for given substring (input_str[0...i])
For the value of the first element the algorithm always returns 0
>>> prefix_function("aabcdaabc")
[0, 1, 0, 0, 0, 1, 2, 3, 4]
>>> prefix_function("asdasdad")
[0, 0, 0, 1, 2, 3, 4, 0]
"""
# list for the result values
prefix_result = [0] * len(input_string)
for i in range(1, len(input_string)):
# use last results for better performance - dynamic programming
j = prefix_result[i - 1]
while j > 0 and input_string[i] != input_string[j]:
j = prefix_result[j - 1]
if input_string[i] == input_string[j]:
j += 1
prefix_result[i] = j
return prefix_result
def longest_prefix(input_str: str) -> int:
"""
Prefix-function use case
Finding longest prefix which is sufix as well
>>> longest_prefix("aabcdaabc")
4
>>> longest_prefix("asdasdad")
4
>>> longest_prefix("abcab")
2
"""
# just returning maximum value of the array gives us answer
return max(prefix_function(input_str))
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
https://cp-algorithms.com/string/prefix-function.html
Prefix function Knuth–Morris–Pratt algorithm
Different algorithm than Knuth-Morris-Pratt pattern finding
E.x. Finding longest prefix which is also suffix
Time Complexity: O(n) - where n is the length of the string
"""
def prefix_function(input_string: str) -> list:
"""
For the given string this function computes value for each index(i),
which represents the longest coincidence of prefix and sufix
for given substring (input_str[0...i])
For the value of the first element the algorithm always returns 0
>>> prefix_function("aabcdaabc")
[0, 1, 0, 0, 0, 1, 2, 3, 4]
>>> prefix_function("asdasdad")
[0, 0, 0, 1, 2, 3, 4, 0]
"""
# list for the result values
prefix_result = [0] * len(input_string)
for i in range(1, len(input_string)):
# use last results for better performance - dynamic programming
j = prefix_result[i - 1]
while j > 0 and input_string[i] != input_string[j]:
j = prefix_result[j - 1]
if input_string[i] == input_string[j]:
j += 1
prefix_result[i] = j
return prefix_result
def longest_prefix(input_str: str) -> int:
"""
Prefix-function use case
Finding longest prefix which is sufix as well
>>> longest_prefix("aabcdaabc")
4
>>> longest_prefix("asdasdad")
4
>>> longest_prefix("abcab")
2
"""
# just returning maximum value of the array gives us answer
return max(prefix_function(input_str))
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Problem 112: https://projecteuler.net/problem=112
Working from left-to-right if no digit is exceeded by the digit to its left it is
called an increasing number; for example, 134468.
Similarly if no digit is exceeded by the digit to its right it is called a decreasing
number; for example, 66420.
We shall call a positive integer that is neither increasing nor decreasing a "bouncy"
number, for example, 155349.
Clearly there cannot be any bouncy numbers below one-hundred, but just over half of
the numbers below one-thousand (525) are bouncy. In fact, the least number for which
the proportion of bouncy numbers first reaches 50% is 538.
Surprisingly, bouncy numbers become more and more common and by the time we reach
21780 the proportion of bouncy numbers is equal to 90%.
Find the least number for which the proportion of bouncy numbers is exactly 99%.
"""
def check_bouncy(n: int) -> bool:
"""
Returns True if number is bouncy, False otherwise
>>> check_bouncy(6789)
False
>>> check_bouncy(-12345)
False
>>> check_bouncy(0)
False
>>> check_bouncy(6.74)
Traceback (most recent call last):
...
ValueError: check_bouncy() accepts only integer arguments
>>> check_bouncy(132475)
True
>>> check_bouncy(34)
False
>>> check_bouncy(341)
True
>>> check_bouncy(47)
False
>>> check_bouncy(-12.54)
Traceback (most recent call last):
...
ValueError: check_bouncy() accepts only integer arguments
>>> check_bouncy(-6548)
True
"""
if not isinstance(n, int):
raise ValueError("check_bouncy() accepts only integer arguments")
return "".join(sorted(str(n))) != str(n) and "".join(sorted(str(n)))[::-1] != str(n)
def solution(percent: float = 99) -> int:
"""
Returns the least number for which the proportion of bouncy numbers is
exactly 'percent'
>>> solution(50)
538
>>> solution(90)
21780
>>> solution(80)
4770
>>> solution(105)
Traceback (most recent call last):
...
ValueError: solution() only accepts values from 0 to 100
>>> solution(100.011)
Traceback (most recent call last):
...
ValueError: solution() only accepts values from 0 to 100
"""
if not 0 < percent < 100:
raise ValueError("solution() only accepts values from 0 to 100")
bouncy_num = 0
num = 1
while True:
if check_bouncy(num):
bouncy_num += 1
if (bouncy_num / num) * 100 >= percent:
return num
num += 1
if __name__ == "__main__":
from doctest import testmod
testmod()
print(f"{solution(99)}")
| """
Problem 112: https://projecteuler.net/problem=112
Working from left-to-right if no digit is exceeded by the digit to its left it is
called an increasing number; for example, 134468.
Similarly if no digit is exceeded by the digit to its right it is called a decreasing
number; for example, 66420.
We shall call a positive integer that is neither increasing nor decreasing a "bouncy"
number, for example, 155349.
Clearly there cannot be any bouncy numbers below one-hundred, but just over half of
the numbers below one-thousand (525) are bouncy. In fact, the least number for which
the proportion of bouncy numbers first reaches 50% is 538.
Surprisingly, bouncy numbers become more and more common and by the time we reach
21780 the proportion of bouncy numbers is equal to 90%.
Find the least number for which the proportion of bouncy numbers is exactly 99%.
"""
def check_bouncy(n: int) -> bool:
"""
Returns True if number is bouncy, False otherwise
>>> check_bouncy(6789)
False
>>> check_bouncy(-12345)
False
>>> check_bouncy(0)
False
>>> check_bouncy(6.74)
Traceback (most recent call last):
...
ValueError: check_bouncy() accepts only integer arguments
>>> check_bouncy(132475)
True
>>> check_bouncy(34)
False
>>> check_bouncy(341)
True
>>> check_bouncy(47)
False
>>> check_bouncy(-12.54)
Traceback (most recent call last):
...
ValueError: check_bouncy() accepts only integer arguments
>>> check_bouncy(-6548)
True
"""
if not isinstance(n, int):
raise ValueError("check_bouncy() accepts only integer arguments")
return "".join(sorted(str(n))) != str(n) and "".join(sorted(str(n)))[::-1] != str(n)
def solution(percent: float = 99) -> int:
"""
Returns the least number for which the proportion of bouncy numbers is
exactly 'percent'
>>> solution(50)
538
>>> solution(90)
21780
>>> solution(80)
4770
>>> solution(105)
Traceback (most recent call last):
...
ValueError: solution() only accepts values from 0 to 100
>>> solution(100.011)
Traceback (most recent call last):
...
ValueError: solution() only accepts values from 0 to 100
"""
if not 0 < percent < 100:
raise ValueError("solution() only accepts values from 0 to 100")
bouncy_num = 0
num = 1
while True:
if check_bouncy(num):
bouncy_num += 1
if (bouncy_num / num) * 100 >= percent:
return num
num += 1
if __name__ == "__main__":
from doctest import testmod
testmod()
print(f"{solution(99)}")
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
This script demonstrates the implementation of the Softmax function.
Its a function that takes as input a vector of K real numbers, and normalizes
it into a probability distribution consisting of K probabilities proportional
to the exponentials of the input numbers. After softmax, the elements of the
vector always sum up to 1.
Script inspired from its corresponding Wikipedia article
https://en.wikipedia.org/wiki/Softmax_function
"""
import numpy as np
def softmax(vector):
"""
Implements the softmax function
Parameters:
vector (np.array,list,tuple): A numpy array of shape (1,n)
consisting of real values or a similar list,tuple
Returns:
softmax_vec (np.array): The input numpy array after applying
softmax.
The softmax vector adds up to one. We need to ceil to mitigate for
precision
>>> np.ceil(np.sum(softmax([1,2,3,4])))
1.0
>>> vec = np.array([5,5])
>>> softmax(vec)
array([0.5, 0.5])
>>> softmax([0])
array([1.])
"""
# Calculate e^x for each x in your vector where e is Euler's
# number (approximately 2.718)
exponentVector = np.exp(vector)
# Add up the all the exponentials
sumOfExponents = np.sum(exponentVector)
# Divide every exponent by the sum of all exponents
softmax_vector = exponentVector / sumOfExponents
return softmax_vector
if __name__ == "__main__":
print(softmax((0,)))
| """
This script demonstrates the implementation of the Softmax function.
Its a function that takes as input a vector of K real numbers, and normalizes
it into a probability distribution consisting of K probabilities proportional
to the exponentials of the input numbers. After softmax, the elements of the
vector always sum up to 1.
Script inspired from its corresponding Wikipedia article
https://en.wikipedia.org/wiki/Softmax_function
"""
import numpy as np
def softmax(vector):
"""
Implements the softmax function
Parameters:
vector (np.array,list,tuple): A numpy array of shape (1,n)
consisting of real values or a similar list,tuple
Returns:
softmax_vec (np.array): The input numpy array after applying
softmax.
The softmax vector adds up to one. We need to ceil to mitigate for
precision
>>> np.ceil(np.sum(softmax([1,2,3,4])))
1.0
>>> vec = np.array([5,5])
>>> softmax(vec)
array([0.5, 0.5])
>>> softmax([0])
array([1.])
"""
# Calculate e^x for each x in your vector where e is Euler's
# number (approximately 2.718)
exponentVector = np.exp(vector)
# Add up the all the exponentials
sumOfExponents = np.sum(exponentVector)
# Divide every exponent by the sum of all exponents
softmax_vector = exponentVector / sumOfExponents
return softmax_vector
if __name__ == "__main__":
print(softmax((0,)))
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # Python program to implement Pigeonhole Sorting in python
# Algorithm for the pigeonhole sorting
def pigeonhole_sort(a):
"""
>>> a = [8, 3, 2, 7, 4, 6, 8]
>>> b = sorted(a) # a nondestructive sort
>>> pigeonhole_sort(a) # a destructive sort
>>> a == b
True
"""
# size of range of values in the list (ie, number of pigeonholes we need)
min_val = min(a) # min() finds the minimum value
max_val = max(a) # max() finds the maximum value
size = max_val - min_val + 1 # size is difference of max and min values plus one
# list of pigeonholes of size equal to the variable size
holes = [0] * size
# Populate the pigeonholes.
for x in a:
assert isinstance(x, int), "integers only please"
holes[x - min_val] += 1
# Putting the elements back into the array in an order.
i = 0
for count in range(size):
while holes[count] > 0:
holes[count] -= 1
a[i] = count + min_val
i += 1
def main():
a = [8, 3, 2, 7, 4, 6, 8]
pigeonhole_sort(a)
print("Sorted order is:", " ".join(a))
if __name__ == "__main__":
main()
| # Python program to implement Pigeonhole Sorting in python
# Algorithm for the pigeonhole sorting
def pigeonhole_sort(a):
"""
>>> a = [8, 3, 2, 7, 4, 6, 8]
>>> b = sorted(a) # a nondestructive sort
>>> pigeonhole_sort(a) # a destructive sort
>>> a == b
True
"""
# size of range of values in the list (ie, number of pigeonholes we need)
min_val = min(a) # min() finds the minimum value
max_val = max(a) # max() finds the maximum value
size = max_val - min_val + 1 # size is difference of max and min values plus one
# list of pigeonholes of size equal to the variable size
holes = [0] * size
# Populate the pigeonholes.
for x in a:
assert isinstance(x, int), "integers only please"
holes[x - min_val] += 1
# Putting the elements back into the array in an order.
i = 0
for count in range(size):
while holes[count] > 0:
holes[count] -= 1
a[i] = count + min_val
i += 1
def main():
a = [8, 3, 2, 7, 4, 6, 8]
pigeonhole_sort(a)
print("Sorted order is:", " ".join(a))
if __name__ == "__main__":
main()
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Finding the peak of a unimodal list using divide and conquer.
A unimodal array is defined as follows: array is increasing up to index p,
then decreasing afterwards. (for p >= 1)
An obvious solution can be performed in O(n),
to find the maximum of the array.
(From Kleinberg and Tardos. Algorithm Design.
Addison Wesley 2006: Chapter 5 Solved Exercise 1)
"""
from typing import List
def peak(lst: List[int]) -> int:
"""
Return the peak value of `lst`.
>>> peak([1, 2, 3, 4, 5, 4, 3, 2, 1])
5
>>> peak([1, 10, 9, 8, 7, 6, 5, 4])
10
>>> peak([1, 9, 8, 7])
9
>>> peak([1, 2, 3, 4, 5, 6, 7, 0])
7
>>> peak([1, 2, 3, 4, 3, 2, 1, 0, -1, -2])
4
"""
# middle index
m = len(lst) // 2
# choose the middle 3 elements
three = lst[m - 1 : m + 2]
# if middle element is peak
if three[1] > three[0] and three[1] > three[2]:
return three[1]
# if increasing, recurse on right
elif three[0] < three[2]:
if len(lst[:m]) == 2:
m -= 1
return peak(lst[m:])
# decreasing
else:
if len(lst[:m]) == 2:
m += 1
return peak(lst[:m])
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
Finding the peak of a unimodal list using divide and conquer.
A unimodal array is defined as follows: array is increasing up to index p,
then decreasing afterwards. (for p >= 1)
An obvious solution can be performed in O(n),
to find the maximum of the array.
(From Kleinberg and Tardos. Algorithm Design.
Addison Wesley 2006: Chapter 5 Solved Exercise 1)
"""
from typing import List
def peak(lst: List[int]) -> int:
"""
Return the peak value of `lst`.
>>> peak([1, 2, 3, 4, 5, 4, 3, 2, 1])
5
>>> peak([1, 10, 9, 8, 7, 6, 5, 4])
10
>>> peak([1, 9, 8, 7])
9
>>> peak([1, 2, 3, 4, 5, 6, 7, 0])
7
>>> peak([1, 2, 3, 4, 3, 2, 1, 0, -1, -2])
4
"""
# middle index
m = len(lst) // 2
# choose the middle 3 elements
three = lst[m - 1 : m + 2]
# if middle element is peak
if three[1] > three[0] and three[1] > three[2]:
return three[1]
# if increasing, recurse on right
elif three[0] < three[2]:
if len(lst[:m]) == 2:
m -= 1
return peak(lst[m:])
# decreasing
else:
if len(lst[:m]) == 2:
m += 1
return peak(lst[:m])
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| class Node:
def __init__(self, data):
self.data = data
self.next = None
def __repr__(self):
return f"Node({self.data})"
class LinkedList:
def __init__(self):
self.head = None
def __iter__(self):
node = self.head
while node:
yield node.data
node = node.next
def __len__(self) -> int:
"""
Return length of linked list i.e. number of nodes
>>> linked_list = LinkedList()
>>> len(linked_list)
0
>>> linked_list.insert_tail("head")
>>> len(linked_list)
1
>>> linked_list.insert_head("head")
>>> len(linked_list)
2
>>> _ = linked_list.delete_tail()
>>> len(linked_list)
1
>>> _ = linked_list.delete_head()
>>> len(linked_list)
0
"""
return len(tuple(iter(self)))
def __repr__(self):
"""
String representation/visualization of a Linked Lists
"""
return "->".join([str(item) for item in self])
def __getitem__(self, index):
"""
Indexing Support. Used to get a node at particular position
>>> linked_list = LinkedList()
>>> for i in range(0, 10):
... linked_list.insert_nth(i, i)
>>> all(str(linked_list[i]) == str(i) for i in range(0, 10))
True
>>> linked_list[-10]
Traceback (most recent call last):
...
ValueError: list index out of range.
>>> linked_list[len(linked_list)]
Traceback (most recent call last):
...
ValueError: list index out of range.
"""
if not 0 <= index < len(self):
raise ValueError("list index out of range.")
for i, node in enumerate(self):
if i == index:
return node
# Used to change the data of a particular node
def __setitem__(self, index, data):
"""
>>> linked_list = LinkedList()
>>> for i in range(0, 10):
... linked_list.insert_nth(i, i)
>>> linked_list[0] = 666
>>> linked_list[0]
666
>>> linked_list[5] = -666
>>> linked_list[5]
-666
>>> linked_list[-10] = 666
Traceback (most recent call last):
...
ValueError: list index out of range.
>>> linked_list[len(linked_list)] = 666
Traceback (most recent call last):
...
ValueError: list index out of range.
"""
if not 0 <= index < len(self):
raise ValueError("list index out of range.")
current = self.head
for i in range(index):
current = current.next
current.data = data
def insert_tail(self, data) -> None:
self.insert_nth(len(self), data)
def insert_head(self, data) -> None:
self.insert_nth(0, data)
def insert_nth(self, index: int, data) -> None:
if not 0 <= index <= len(self):
raise IndexError("list index out of range")
new_node = Node(data)
if self.head is None:
self.head = new_node
elif index == 0:
new_node.next = self.head # link new_node to head
self.head = new_node
else:
temp = self.head
for _ in range(index - 1):
temp = temp.next
new_node.next = temp.next
temp.next = new_node
def print_list(self) -> None: # print every node data
print(self)
def delete_head(self):
return self.delete_nth(0)
def delete_tail(self): # delete from tail
return self.delete_nth(len(self) - 1)
def delete_nth(self, index: int = 0):
if not 0 <= index <= len(self) - 1: # test if index is valid
raise IndexError("list index out of range")
delete_node = self.head # default first node
if index == 0:
self.head = self.head.next
else:
temp = self.head
for _ in range(index - 1):
temp = temp.next
delete_node = temp.next
temp.next = temp.next.next
return delete_node.data
def is_empty(self) -> bool:
return self.head is None
def reverse(self):
prev = None
current = self.head
while current:
# Store the current node's next node.
next_node = current.next
# Make the current node's next point backwards
current.next = prev
# Make the previous node be the current node
prev = current
# Make the current node the next node (to progress iteration)
current = next_node
# Return prev in order to put the head at the end
self.head = prev
def test_singly_linked_list() -> None:
"""
>>> test_singly_linked_list()
"""
linked_list = LinkedList()
assert linked_list.is_empty() is True
assert str(linked_list) == ""
try:
linked_list.delete_head()
assert False # This should not happen.
except IndexError:
assert True # This should happen.
try:
linked_list.delete_tail()
assert False # This should not happen.
except IndexError:
assert True # This should happen.
for i in range(10):
assert len(linked_list) == i
linked_list.insert_nth(i, i + 1)
assert str(linked_list) == "->".join(str(i) for i in range(1, 11))
linked_list.insert_head(0)
linked_list.insert_tail(11)
assert str(linked_list) == "->".join(str(i) for i in range(0, 12))
assert linked_list.delete_head() == 0
assert linked_list.delete_nth(9) == 10
assert linked_list.delete_tail() == 11
assert len(linked_list) == 9
assert str(linked_list) == "->".join(str(i) for i in range(1, 10))
assert all(linked_list[i] == i + 1 for i in range(0, 9)) is True
for i in range(0, 9):
linked_list[i] = -i
assert all(linked_list[i] == -i for i in range(0, 9)) is True
def main():
from doctest import testmod
testmod()
linked_list = LinkedList()
linked_list.insert_head(input("Inserting 1st at head ").strip())
linked_list.insert_head(input("Inserting 2nd at head ").strip())
print("\nPrint list:")
linked_list.print_list()
linked_list.insert_tail(input("\nInserting 1st at tail ").strip())
linked_list.insert_tail(input("Inserting 2nd at tail ").strip())
print("\nPrint list:")
linked_list.print_list()
print("\nDelete head")
linked_list.delete_head()
print("Delete tail")
linked_list.delete_tail()
print("\nPrint list:")
linked_list.print_list()
print("\nReverse linked list")
linked_list.reverse()
print("\nPrint list:")
linked_list.print_list()
print("\nString representation of linked list:")
print(linked_list)
print("\nReading/changing Node data using indexing:")
print(f"Element at Position 1: {linked_list[1]}")
linked_list[1] = input("Enter New Value: ").strip()
print("New list:")
print(linked_list)
print(f"length of linked_list is : {len(linked_list)}")
if __name__ == "__main__":
main()
| class Node:
def __init__(self, data):
self.data = data
self.next = None
def __repr__(self):
return f"Node({self.data})"
class LinkedList:
def __init__(self):
self.head = None
def __iter__(self):
node = self.head
while node:
yield node.data
node = node.next
def __len__(self) -> int:
"""
Return length of linked list i.e. number of nodes
>>> linked_list = LinkedList()
>>> len(linked_list)
0
>>> linked_list.insert_tail("head")
>>> len(linked_list)
1
>>> linked_list.insert_head("head")
>>> len(linked_list)
2
>>> _ = linked_list.delete_tail()
>>> len(linked_list)
1
>>> _ = linked_list.delete_head()
>>> len(linked_list)
0
"""
return len(tuple(iter(self)))
def __repr__(self):
"""
String representation/visualization of a Linked Lists
"""
return "->".join([str(item) for item in self])
def __getitem__(self, index):
"""
Indexing Support. Used to get a node at particular position
>>> linked_list = LinkedList()
>>> for i in range(0, 10):
... linked_list.insert_nth(i, i)
>>> all(str(linked_list[i]) == str(i) for i in range(0, 10))
True
>>> linked_list[-10]
Traceback (most recent call last):
...
ValueError: list index out of range.
>>> linked_list[len(linked_list)]
Traceback (most recent call last):
...
ValueError: list index out of range.
"""
if not 0 <= index < len(self):
raise ValueError("list index out of range.")
for i, node in enumerate(self):
if i == index:
return node
# Used to change the data of a particular node
def __setitem__(self, index, data):
"""
>>> linked_list = LinkedList()
>>> for i in range(0, 10):
... linked_list.insert_nth(i, i)
>>> linked_list[0] = 666
>>> linked_list[0]
666
>>> linked_list[5] = -666
>>> linked_list[5]
-666
>>> linked_list[-10] = 666
Traceback (most recent call last):
...
ValueError: list index out of range.
>>> linked_list[len(linked_list)] = 666
Traceback (most recent call last):
...
ValueError: list index out of range.
"""
if not 0 <= index < len(self):
raise ValueError("list index out of range.")
current = self.head
for i in range(index):
current = current.next
current.data = data
def insert_tail(self, data) -> None:
self.insert_nth(len(self), data)
def insert_head(self, data) -> None:
self.insert_nth(0, data)
def insert_nth(self, index: int, data) -> None:
if not 0 <= index <= len(self):
raise IndexError("list index out of range")
new_node = Node(data)
if self.head is None:
self.head = new_node
elif index == 0:
new_node.next = self.head # link new_node to head
self.head = new_node
else:
temp = self.head
for _ in range(index - 1):
temp = temp.next
new_node.next = temp.next
temp.next = new_node
def print_list(self) -> None: # print every node data
print(self)
def delete_head(self):
return self.delete_nth(0)
def delete_tail(self): # delete from tail
return self.delete_nth(len(self) - 1)
def delete_nth(self, index: int = 0):
if not 0 <= index <= len(self) - 1: # test if index is valid
raise IndexError("list index out of range")
delete_node = self.head # default first node
if index == 0:
self.head = self.head.next
else:
temp = self.head
for _ in range(index - 1):
temp = temp.next
delete_node = temp.next
temp.next = temp.next.next
return delete_node.data
def is_empty(self) -> bool:
return self.head is None
def reverse(self):
prev = None
current = self.head
while current:
# Store the current node's next node.
next_node = current.next
# Make the current node's next point backwards
current.next = prev
# Make the previous node be the current node
prev = current
# Make the current node the next node (to progress iteration)
current = next_node
# Return prev in order to put the head at the end
self.head = prev
def test_singly_linked_list() -> None:
"""
>>> test_singly_linked_list()
"""
linked_list = LinkedList()
assert linked_list.is_empty() is True
assert str(linked_list) == ""
try:
linked_list.delete_head()
assert False # This should not happen.
except IndexError:
assert True # This should happen.
try:
linked_list.delete_tail()
assert False # This should not happen.
except IndexError:
assert True # This should happen.
for i in range(10):
assert len(linked_list) == i
linked_list.insert_nth(i, i + 1)
assert str(linked_list) == "->".join(str(i) for i in range(1, 11))
linked_list.insert_head(0)
linked_list.insert_tail(11)
assert str(linked_list) == "->".join(str(i) for i in range(0, 12))
assert linked_list.delete_head() == 0
assert linked_list.delete_nth(9) == 10
assert linked_list.delete_tail() == 11
assert len(linked_list) == 9
assert str(linked_list) == "->".join(str(i) for i in range(1, 10))
assert all(linked_list[i] == i + 1 for i in range(0, 9)) is True
for i in range(0, 9):
linked_list[i] = -i
assert all(linked_list[i] == -i for i in range(0, 9)) is True
def main():
from doctest import testmod
testmod()
linked_list = LinkedList()
linked_list.insert_head(input("Inserting 1st at head ").strip())
linked_list.insert_head(input("Inserting 2nd at head ").strip())
print("\nPrint list:")
linked_list.print_list()
linked_list.insert_tail(input("\nInserting 1st at tail ").strip())
linked_list.insert_tail(input("Inserting 2nd at tail ").strip())
print("\nPrint list:")
linked_list.print_list()
print("\nDelete head")
linked_list.delete_head()
print("Delete tail")
linked_list.delete_tail()
print("\nPrint list:")
linked_list.print_list()
print("\nReverse linked list")
linked_list.reverse()
print("\nPrint list:")
linked_list.print_list()
print("\nString representation of linked list:")
print(linked_list)
print("\nReading/changing Node data using indexing:")
print(f"Element at Position 1: {linked_list[1]}")
linked_list[1] = input("Enter New Value: ").strip()
print("New list:")
print(linked_list)
print(f"length of linked_list is : {len(linked_list)}")
if __name__ == "__main__":
main()
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| def get_word_pattern(word: str) -> str:
"""
>>> get_word_pattern("pattern")
'0.1.2.2.3.4.5'
>>> get_word_pattern("word pattern")
'0.1.2.3.4.5.6.7.7.8.2.9'
>>> get_word_pattern("get word pattern")
'0.1.2.3.4.5.6.7.3.8.9.2.2.1.6.10'
"""
word = word.upper()
next_num = 0
letter_nums = {}
word_pattern = []
for letter in word:
if letter not in letter_nums:
letter_nums[letter] = str(next_num)
next_num += 1
word_pattern.append(letter_nums[letter])
return ".".join(word_pattern)
if __name__ == "__main__":
import pprint
import time
start_time = time.time()
with open("dictionary.txt") as in_file:
wordList = in_file.read().splitlines()
all_patterns = {}
for word in wordList:
pattern = get_word_pattern(word)
if pattern in all_patterns:
all_patterns[pattern].append(word)
else:
all_patterns[pattern] = [word]
with open("word_patterns.txt", "w") as out_file:
out_file.write(pprint.pformat(all_patterns))
totalTime = round(time.time() - start_time, 2)
print(f"Done! {len(all_patterns):,} word patterns found in {totalTime} seconds.")
# Done! 9,581 word patterns found in 0.58 seconds.
| def get_word_pattern(word: str) -> str:
"""
>>> get_word_pattern("pattern")
'0.1.2.2.3.4.5'
>>> get_word_pattern("word pattern")
'0.1.2.3.4.5.6.7.7.8.2.9'
>>> get_word_pattern("get word pattern")
'0.1.2.3.4.5.6.7.3.8.9.2.2.1.6.10'
"""
word = word.upper()
next_num = 0
letter_nums = {}
word_pattern = []
for letter in word:
if letter not in letter_nums:
letter_nums[letter] = str(next_num)
next_num += 1
word_pattern.append(letter_nums[letter])
return ".".join(word_pattern)
if __name__ == "__main__":
import pprint
import time
start_time = time.time()
with open("dictionary.txt") as in_file:
wordList = in_file.read().splitlines()
all_patterns = {}
for word in wordList:
pattern = get_word_pattern(word)
if pattern in all_patterns:
all_patterns[pattern].append(word)
else:
all_patterns[pattern] = [word]
with open("word_patterns.txt", "w") as out_file:
out_file.write(pprint.pformat(all_patterns))
totalTime = round(time.time() - start_time, 2)
print(f"Done! {len(all_patterns):,} word patterns found in {totalTime} seconds.")
# Done! 9,581 word patterns found in 0.58 seconds.
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # NguyenU
def find_max(nums):
"""
>>> for nums in ([3, 2, 1], [-3, -2, -1], [3, -3, 0], [3.0, 3.1, 2.9]):
... find_max(nums) == max(nums)
True
True
True
True
"""
max_num = nums[0]
for x in nums:
if x > max_num:
max_num = x
return max_num
def main():
print(find_max([2, 4, 9, 7, 19, 94, 5])) # 94
if __name__ == "__main__":
main()
| # NguyenU
def find_max(nums):
"""
>>> for nums in ([3, 2, 1], [-3, -2, -1], [3, -3, 0], [3.0, 3.1, 2.9]):
... find_max(nums) == max(nums)
True
True
True
True
"""
max_num = nums[0]
for x in nums:
if x > max_num:
max_num = x
return max_num
def main():
print(find_max([2, 4, 9, 7, 19, 94, 5])) # 94
if __name__ == "__main__":
main()
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Implements a disjoint set using Lists and some added heuristics for efficiency
Union by Rank Heuristic and Path Compression
"""
class DisjointSet:
def __init__(self, set_counts: list) -> None:
"""
Initialize with a list of the number of items in each set
and with rank = 1 for each set
"""
self.set_counts = set_counts
self.max_set = max(set_counts)
num_sets = len(set_counts)
self.ranks = [1] * num_sets
self.parents = list(range(num_sets))
def merge(self, src: int, dst: int) -> bool:
"""
Merge two sets together using Union by rank heuristic
Return True if successful
Merge two disjoint sets
>>> A = DisjointSet([1, 1, 1])
>>> A.merge(1, 2)
True
>>> A.merge(0, 2)
True
>>> A.merge(0, 1)
False
"""
src_parent = self.get_parent(src)
dst_parent = self.get_parent(dst)
if src_parent == dst_parent:
return False
if self.ranks[dst_parent] >= self.ranks[src_parent]:
self.set_counts[dst_parent] += self.set_counts[src_parent]
self.set_counts[src_parent] = 0
self.parents[src_parent] = dst_parent
if self.ranks[dst_parent] == self.ranks[src_parent]:
self.ranks[dst_parent] += 1
joined_set_size = self.set_counts[dst_parent]
else:
self.set_counts[src_parent] += self.set_counts[dst_parent]
self.set_counts[dst_parent] = 0
self.parents[dst_parent] = src_parent
joined_set_size = self.set_counts[src_parent]
self.max_set = max(self.max_set, joined_set_size)
return True
def get_parent(self, disj_set: int) -> int:
"""
Find the Parent of a given set
>>> A = DisjointSet([1, 1, 1])
>>> A.merge(1, 2)
True
>>> A.get_parent(0)
0
>>> A.get_parent(1)
2
"""
if self.parents[disj_set] == disj_set:
return disj_set
self.parents[disj_set] = self.get_parent(self.parents[disj_set])
return self.parents[disj_set]
| """
Implements a disjoint set using Lists and some added heuristics for efficiency
Union by Rank Heuristic and Path Compression
"""
class DisjointSet:
def __init__(self, set_counts: list) -> None:
"""
Initialize with a list of the number of items in each set
and with rank = 1 for each set
"""
self.set_counts = set_counts
self.max_set = max(set_counts)
num_sets = len(set_counts)
self.ranks = [1] * num_sets
self.parents = list(range(num_sets))
def merge(self, src: int, dst: int) -> bool:
"""
Merge two sets together using Union by rank heuristic
Return True if successful
Merge two disjoint sets
>>> A = DisjointSet([1, 1, 1])
>>> A.merge(1, 2)
True
>>> A.merge(0, 2)
True
>>> A.merge(0, 1)
False
"""
src_parent = self.get_parent(src)
dst_parent = self.get_parent(dst)
if src_parent == dst_parent:
return False
if self.ranks[dst_parent] >= self.ranks[src_parent]:
self.set_counts[dst_parent] += self.set_counts[src_parent]
self.set_counts[src_parent] = 0
self.parents[src_parent] = dst_parent
if self.ranks[dst_parent] == self.ranks[src_parent]:
self.ranks[dst_parent] += 1
joined_set_size = self.set_counts[dst_parent]
else:
self.set_counts[src_parent] += self.set_counts[dst_parent]
self.set_counts[dst_parent] = 0
self.parents[dst_parent] = src_parent
joined_set_size = self.set_counts[src_parent]
self.max_set = max(self.max_set, joined_set_size)
return True
def get_parent(self, disj_set: int) -> int:
"""
Find the Parent of a given set
>>> A = DisjointSet([1, 1, 1])
>>> A.merge(1, 2)
True
>>> A.get_parent(0)
0
>>> A.get_parent(1)
2
"""
if self.parents[disj_set] == disj_set:
return disj_set
self.parents[disj_set] = self.get_parent(self.parents[disj_set])
return self.parents[disj_set]
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| def remove_duplicates(key: str) -> str:
"""
Removes duplicate alphabetic characters in a keyword (letter is ignored after its
first appearance).
:param key: Keyword to use
:return: String with duplicates removed
>>> remove_duplicates('Hello World!!')
'Helo Wrd'
"""
key_no_dups = ""
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def create_cipher_map(key: str) -> dict:
"""
Returns a cipher map given a keyword.
:param key: keyword to use
:return: dictionary cipher map
"""
# Create alphabet list
alphabet = [chr(i + 65) for i in range(26)]
# Remove duplicate characters from key
key = remove_duplicates(key.upper())
offset = len(key)
# First fill cipher with key characters
cipher_alphabet = {alphabet[i]: char for i, char in enumerate(key)}
# Then map remaining characters in alphabet to
# the alphabet from the beginning
for i in range(len(cipher_alphabet), 26):
char = alphabet[i - offset]
# Ensure we are not mapping letters to letters previously mapped
while char in key:
offset -= 1
char = alphabet[i - offset]
cipher_alphabet[alphabet[i]] = char
return cipher_alphabet
def encipher(message: str, cipher_map: dict) -> str:
"""
Enciphers a message given a cipher map.
:param message: Message to encipher
:param cipher_map: Cipher map
:return: enciphered string
>>> encipher('Hello World!!', create_cipher_map('Goodbye!!'))
'CYJJM VMQJB!!'
"""
return "".join(cipher_map.get(ch, ch) for ch in message.upper())
def decipher(message: str, cipher_map: dict) -> str:
"""
Deciphers a message given a cipher map
:param message: Message to decipher
:param cipher_map: Dictionary mapping to use
:return: Deciphered string
>>> cipher_map = create_cipher_map('Goodbye!!')
>>> decipher(encipher('Hello World!!', cipher_map), cipher_map)
'HELLO WORLD!!'
"""
# Reverse our cipher mappings
rev_cipher_map = {v: k for k, v in cipher_map.items()}
return "".join(rev_cipher_map.get(ch, ch) for ch in message.upper())
def main():
"""
Handles I/O
:return: void
"""
message = input("Enter message to encode or decode: ").strip()
key = input("Enter keyword: ").strip()
option = input("Encipher or decipher? E/D:").strip()[0].lower()
try:
func = {"e": encipher, "d": decipher}[option]
except KeyError:
raise KeyError("invalid input option")
cipher_map = create_cipher_map(key)
print(func(message, cipher_map))
if __name__ == "__main__":
import doctest
doctest.testmod()
main()
| def remove_duplicates(key: str) -> str:
"""
Removes duplicate alphabetic characters in a keyword (letter is ignored after its
first appearance).
:param key: Keyword to use
:return: String with duplicates removed
>>> remove_duplicates('Hello World!!')
'Helo Wrd'
"""
key_no_dups = ""
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def create_cipher_map(key: str) -> dict:
"""
Returns a cipher map given a keyword.
:param key: keyword to use
:return: dictionary cipher map
"""
# Create alphabet list
alphabet = [chr(i + 65) for i in range(26)]
# Remove duplicate characters from key
key = remove_duplicates(key.upper())
offset = len(key)
# First fill cipher with key characters
cipher_alphabet = {alphabet[i]: char for i, char in enumerate(key)}
# Then map remaining characters in alphabet to
# the alphabet from the beginning
for i in range(len(cipher_alphabet), 26):
char = alphabet[i - offset]
# Ensure we are not mapping letters to letters previously mapped
while char in key:
offset -= 1
char = alphabet[i - offset]
cipher_alphabet[alphabet[i]] = char
return cipher_alphabet
def encipher(message: str, cipher_map: dict) -> str:
"""
Enciphers a message given a cipher map.
:param message: Message to encipher
:param cipher_map: Cipher map
:return: enciphered string
>>> encipher('Hello World!!', create_cipher_map('Goodbye!!'))
'CYJJM VMQJB!!'
"""
return "".join(cipher_map.get(ch, ch) for ch in message.upper())
def decipher(message: str, cipher_map: dict) -> str:
"""
Deciphers a message given a cipher map
:param message: Message to decipher
:param cipher_map: Dictionary mapping to use
:return: Deciphered string
>>> cipher_map = create_cipher_map('Goodbye!!')
>>> decipher(encipher('Hello World!!', cipher_map), cipher_map)
'HELLO WORLD!!'
"""
# Reverse our cipher mappings
rev_cipher_map = {v: k for k, v in cipher_map.items()}
return "".join(rev_cipher_map.get(ch, ch) for ch in message.upper())
def main():
"""
Handles I/O
:return: void
"""
message = input("Enter message to encode or decode: ").strip()
key = input("Enter keyword: ").strip()
option = input("Encipher or decipher? E/D:").strip()[0].lower()
try:
func = {"e": encipher, "d": decipher}[option]
except KeyError:
raise KeyError("invalid input option")
cipher_map = create_cipher_map(key)
print(func(message, cipher_map))
if __name__ == "__main__":
import doctest
doctest.testmod()
main()
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
This algorithm helps you to swap cases.
User will give input and then program will perform swap cases.
In other words, convert all lowercase letters to uppercase letters and vice versa.
For example:
1. Please input sentence: Algorithm.Python@89
aLGORITHM.pYTHON@89
2. Please input sentence: github.com/mayur200
GITHUB.COM/MAYUR200
"""
def swap_case(sentence: str) -> str:
"""
This function will convert all lowercase letters to uppercase letters
and vice versa.
>>> swap_case('Algorithm.Python@89')
'aLGORITHM.pYTHON@89'
"""
new_string = ""
for char in sentence:
if char.isupper():
new_string += char.lower()
elif char.islower():
new_string += char.upper()
else:
new_string += char
return new_string
if __name__ == "__main__":
print(swap_case(input("Please input sentence: ")))
| """
This algorithm helps you to swap cases.
User will give input and then program will perform swap cases.
In other words, convert all lowercase letters to uppercase letters and vice versa.
For example:
1. Please input sentence: Algorithm.Python@89
aLGORITHM.pYTHON@89
2. Please input sentence: github.com/mayur200
GITHUB.COM/MAYUR200
"""
def swap_case(sentence: str) -> str:
"""
This function will convert all lowercase letters to uppercase letters
and vice versa.
>>> swap_case('Algorithm.Python@89')
'aLGORITHM.pYTHON@89'
"""
new_string = ""
for char in sentence:
if char.isupper():
new_string += char.lower()
elif char.islower():
new_string += char.upper()
else:
new_string += char
return new_string
if __name__ == "__main__":
print(swap_case(input("Please input sentence: ")))
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 35
https://projecteuler.net/problem=35
Problem Statement:
The number 197 is called a circular prime because all rotations of the digits:
197, 971, and 719, are themselves prime.
There are thirteen such primes below 100: 2, 3, 5, 7, 11, 13, 17, 31, 37, 71, 73,
79, and 97.
How many circular primes are there below one million?
To solve this problem in an efficient manner, we will first mark all the primes
below 1 million using the Seive of Eratosthenes. Then, out of all these primes,
we will rule out the numbers which contain an even digit. After this we will
generate each circular combination of the number and check if all are prime.
"""
from __future__ import annotations
seive = [True] * 1000001
i = 2
while i * i <= 1000000:
if seive[i]:
for j in range(i * i, 1000001, i):
seive[j] = False
i += 1
def is_prime(n: int) -> bool:
"""
For 2 <= n <= 1000000, return True if n is prime.
>>> is_prime(87)
False
>>> is_prime(23)
True
>>> is_prime(25363)
False
"""
return seive[n]
def contains_an_even_digit(n: int) -> bool:
"""
Return True if n contains an even digit.
>>> contains_an_even_digit(0)
True
>>> contains_an_even_digit(975317933)
False
>>> contains_an_even_digit(-245679)
True
"""
return any(digit in "02468" for digit in str(n))
def find_circular_primes(limit: int = 1000000) -> list[int]:
"""
Return circular primes below limit.
>>> len(find_circular_primes(100))
13
>>> len(find_circular_primes(1000000))
55
"""
result = [2] # result already includes the number 2.
for num in range(3, limit + 1, 2):
if is_prime(num) and not contains_an_even_digit(num):
str_num = str(num)
list_nums = [int(str_num[j:] + str_num[:j]) for j in range(len(str_num))]
if all(is_prime(i) for i in list_nums):
result.append(num)
return result
def solution() -> int:
"""
>>> solution()
55
"""
return len(find_circular_primes())
if __name__ == "__main__":
print(f"{len(find_circular_primes()) = }")
| """
Project Euler Problem 35
https://projecteuler.net/problem=35
Problem Statement:
The number 197 is called a circular prime because all rotations of the digits:
197, 971, and 719, are themselves prime.
There are thirteen such primes below 100: 2, 3, 5, 7, 11, 13, 17, 31, 37, 71, 73,
79, and 97.
How many circular primes are there below one million?
To solve this problem in an efficient manner, we will first mark all the primes
below 1 million using the Seive of Eratosthenes. Then, out of all these primes,
we will rule out the numbers which contain an even digit. After this we will
generate each circular combination of the number and check if all are prime.
"""
from __future__ import annotations
seive = [True] * 1000001
i = 2
while i * i <= 1000000:
if seive[i]:
for j in range(i * i, 1000001, i):
seive[j] = False
i += 1
def is_prime(n: int) -> bool:
"""
For 2 <= n <= 1000000, return True if n is prime.
>>> is_prime(87)
False
>>> is_prime(23)
True
>>> is_prime(25363)
False
"""
return seive[n]
def contains_an_even_digit(n: int) -> bool:
"""
Return True if n contains an even digit.
>>> contains_an_even_digit(0)
True
>>> contains_an_even_digit(975317933)
False
>>> contains_an_even_digit(-245679)
True
"""
return any(digit in "02468" for digit in str(n))
def find_circular_primes(limit: int = 1000000) -> list[int]:
"""
Return circular primes below limit.
>>> len(find_circular_primes(100))
13
>>> len(find_circular_primes(1000000))
55
"""
result = [2] # result already includes the number 2.
for num in range(3, limit + 1, 2):
if is_prime(num) and not contains_an_even_digit(num):
str_num = str(num)
list_nums = [int(str_num[j:] + str_num[:j]) for j in range(len(str_num))]
if all(is_prime(i) for i in list_nums):
result.append(num)
return result
def solution() -> int:
"""
>>> solution()
55
"""
return len(find_circular_primes())
if __name__ == "__main__":
print(f"{len(find_circular_primes()) = }")
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Python3 program to evaluate a prefix expression.
"""
calc = {
"+": lambda x, y: x + y,
"-": lambda x, y: x - y,
"*": lambda x, y: x * y,
"/": lambda x, y: x / y,
}
def is_operand(c):
"""
Return True if the given char c is an operand, e.g. it is a number
>>> is_operand("1")
True
>>> is_operand("+")
False
"""
return c.isdigit()
def evaluate(expression):
"""
Evaluate a given expression in prefix notation.
Asserts that the given expression is valid.
>>> evaluate("+ 9 * 2 6")
21
>>> evaluate("/ * 10 2 + 4 1 ")
4.0
"""
stack = []
# iterate over the string in reverse order
for c in expression.split()[::-1]:
# push operand to stack
if is_operand(c):
stack.append(int(c))
else:
# pop values from stack can calculate the result
# push the result onto the stack again
o1 = stack.pop()
o2 = stack.pop()
stack.append(calc[c](o1, o2))
return stack.pop()
# Driver code
if __name__ == "__main__":
test_expression = "+ 9 * 2 6"
print(evaluate(test_expression))
test_expression = "/ * 10 2 + 4 1 "
print(evaluate(test_expression))
| """
Python3 program to evaluate a prefix expression.
"""
calc = {
"+": lambda x, y: x + y,
"-": lambda x, y: x - y,
"*": lambda x, y: x * y,
"/": lambda x, y: x / y,
}
def is_operand(c):
"""
Return True if the given char c is an operand, e.g. it is a number
>>> is_operand("1")
True
>>> is_operand("+")
False
"""
return c.isdigit()
def evaluate(expression):
"""
Evaluate a given expression in prefix notation.
Asserts that the given expression is valid.
>>> evaluate("+ 9 * 2 6")
21
>>> evaluate("/ * 10 2 + 4 1 ")
4.0
"""
stack = []
# iterate over the string in reverse order
for c in expression.split()[::-1]:
# push operand to stack
if is_operand(c):
stack.append(int(c))
else:
# pop values from stack can calculate the result
# push the result onto the stack again
o1 = stack.pop()
o2 = stack.pop()
stack.append(calc[c](o1, o2))
return stack.pop()
# Driver code
if __name__ == "__main__":
test_expression = "+ 9 * 2 6"
print(evaluate(test_expression))
test_expression = "/ * 10 2 + 4 1 "
print(evaluate(test_expression))
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 4: https://projecteuler.net/problem=4
Largest palindrome product
A palindromic number reads the same both ways. The largest palindrome made
from the product of two 2-digit numbers is 9009 = 91 × 99.
Find the largest palindrome made from the product of two 3-digit numbers.
References:
- https://en.wikipedia.org/wiki/Palindromic_number
"""
def solution(n: int = 998001) -> int:
"""
Returns the largest palindrome made from the product of two 3-digit
numbers which is less than n.
>>> solution(20000)
19591
>>> solution(30000)
29992
>>> solution(40000)
39893
"""
answer = 0
for i in range(999, 99, -1): # 3 digit numbers range from 999 down to 100
for j in range(999, 99, -1):
product_string = str(i * j)
if product_string == product_string[::-1] and i * j < n:
answer = max(answer, i * j)
return answer
if __name__ == "__main__":
print(f"{solution() = }")
| """
Project Euler Problem 4: https://projecteuler.net/problem=4
Largest palindrome product
A palindromic number reads the same both ways. The largest palindrome made
from the product of two 2-digit numbers is 9009 = 91 × 99.
Find the largest palindrome made from the product of two 3-digit numbers.
References:
- https://en.wikipedia.org/wiki/Palindromic_number
"""
def solution(n: int = 998001) -> int:
"""
Returns the largest palindrome made from the product of two 3-digit
numbers which is less than n.
>>> solution(20000)
19591
>>> solution(30000)
29992
>>> solution(40000)
39893
"""
answer = 0
for i in range(999, 99, -1): # 3 digit numbers range from 999 down to 100
for j in range(999, 99, -1):
product_string = str(i * j)
if product_string == product_string[::-1] and i * j < n:
answer = max(answer, i * j)
return answer
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
https://en.wikipedia.org/wiki/Doubly_linked_list
"""
class Node:
def __init__(self, data):
self.data = data
self.previous = None
self.next = None
def __str__(self):
return f"{self.data}"
class DoublyLinkedList:
def __init__(self):
self.head = None
self.tail = None
def __iter__(self):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.insert_at_head('b')
>>> linked_list.insert_at_head('a')
>>> linked_list.insert_at_tail('c')
>>> tuple(linked_list)
('a', 'b', 'c')
"""
node = self.head
while node:
yield node.data
node = node.next
def __str__(self):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.insert_at_tail('a')
>>> linked_list.insert_at_tail('b')
>>> linked_list.insert_at_tail('c')
>>> str(linked_list)
'a->b->c'
"""
return "->".join([str(item) for item in self])
def __len__(self):
"""
>>> linked_list = DoublyLinkedList()
>>> for i in range(0, 5):
... linked_list.insert_at_nth(i, i + 1)
>>> len(linked_list) == 5
True
"""
return len(tuple(iter(self)))
def insert_at_head(self, data):
self.insert_at_nth(0, data)
def insert_at_tail(self, data):
self.insert_at_nth(len(self), data)
def insert_at_nth(self, index: int, data):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.insert_at_nth(-1, 666)
Traceback (most recent call last):
....
IndexError: list index out of range
>>> linked_list.insert_at_nth(1, 666)
Traceback (most recent call last):
....
IndexError: list index out of range
>>> linked_list.insert_at_nth(0, 2)
>>> linked_list.insert_at_nth(0, 1)
>>> linked_list.insert_at_nth(2, 4)
>>> linked_list.insert_at_nth(2, 3)
>>> str(linked_list)
'1->2->3->4'
>>> linked_list.insert_at_nth(5, 5)
Traceback (most recent call last):
....
IndexError: list index out of range
"""
if not 0 <= index <= len(self):
raise IndexError("list index out of range")
new_node = Node(data)
if self.head is None:
self.head = self.tail = new_node
elif index == 0:
self.head.previous = new_node
new_node.next = self.head
self.head = new_node
elif index == len(self):
self.tail.next = new_node
new_node.previous = self.tail
self.tail = new_node
else:
temp = self.head
for i in range(0, index):
temp = temp.next
temp.previous.next = new_node
new_node.previous = temp.previous
new_node.next = temp
temp.previous = new_node
def delete_head(self):
return self.delete_at_nth(0)
def delete_tail(self):
return self.delete_at_nth(len(self) - 1)
def delete_at_nth(self, index: int):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.delete_at_nth(0)
Traceback (most recent call last):
....
IndexError: list index out of range
>>> for i in range(0, 5):
... linked_list.insert_at_nth(i, i + 1)
>>> linked_list.delete_at_nth(0) == 1
True
>>> linked_list.delete_at_nth(3) == 5
True
>>> linked_list.delete_at_nth(1) == 3
True
>>> str(linked_list)
'2->4'
>>> linked_list.delete_at_nth(2)
Traceback (most recent call last):
....
IndexError: list index out of range
"""
if not 0 <= index <= len(self) - 1:
raise IndexError("list index out of range")
delete_node = self.head # default first node
if len(self) == 1:
self.head = self.tail = None
elif index == 0:
self.head = self.head.next
self.head.previous = None
elif index == len(self) - 1:
delete_node = self.tail
self.tail = self.tail.previous
self.tail.next = None
else:
temp = self.head
for i in range(0, index):
temp = temp.next
delete_node = temp
temp.next.previous = temp.previous
temp.previous.next = temp.next
return delete_node.data
def delete(self, data) -> str:
current = self.head
while current.data != data: # Find the position to delete
if current.next:
current = current.next
else: # We have reached the end an no value matches
return "No data matching given value"
if current == self.head:
self.delete_head()
elif current == self.tail:
self.delete_tail()
else: # Before: 1 <--> 2(current) <--> 3
current.previous.next = current.next # 1 --> 3
current.next.previous = current.previous # 1 <--> 3
return data
def is_empty(self):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.is_empty()
True
>>> linked_list.insert_at_tail(1)
>>> linked_list.is_empty()
False
"""
return len(self) == 0
def test_doubly_linked_list() -> None:
"""
>>> test_doubly_linked_list()
"""
linked_list = DoublyLinkedList()
assert linked_list.is_empty() is True
assert str(linked_list) == ""
try:
linked_list.delete_head()
assert False # This should not happen.
except IndexError:
assert True # This should happen.
try:
linked_list.delete_tail()
assert False # This should not happen.
except IndexError:
assert True # This should happen.
for i in range(10):
assert len(linked_list) == i
linked_list.insert_at_nth(i, i + 1)
assert str(linked_list) == "->".join(str(i) for i in range(1, 11))
linked_list.insert_at_head(0)
linked_list.insert_at_tail(11)
assert str(linked_list) == "->".join(str(i) for i in range(0, 12))
assert linked_list.delete_head() == 0
assert linked_list.delete_at_nth(9) == 10
assert linked_list.delete_tail() == 11
assert len(linked_list) == 9
assert str(linked_list) == "->".join(str(i) for i in range(1, 10))
if __name__ == "__main__":
from doctest import testmod
testmod()
| """
https://en.wikipedia.org/wiki/Doubly_linked_list
"""
class Node:
def __init__(self, data):
self.data = data
self.previous = None
self.next = None
def __str__(self):
return f"{self.data}"
class DoublyLinkedList:
def __init__(self):
self.head = None
self.tail = None
def __iter__(self):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.insert_at_head('b')
>>> linked_list.insert_at_head('a')
>>> linked_list.insert_at_tail('c')
>>> tuple(linked_list)
('a', 'b', 'c')
"""
node = self.head
while node:
yield node.data
node = node.next
def __str__(self):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.insert_at_tail('a')
>>> linked_list.insert_at_tail('b')
>>> linked_list.insert_at_tail('c')
>>> str(linked_list)
'a->b->c'
"""
return "->".join([str(item) for item in self])
def __len__(self):
"""
>>> linked_list = DoublyLinkedList()
>>> for i in range(0, 5):
... linked_list.insert_at_nth(i, i + 1)
>>> len(linked_list) == 5
True
"""
return len(tuple(iter(self)))
def insert_at_head(self, data):
self.insert_at_nth(0, data)
def insert_at_tail(self, data):
self.insert_at_nth(len(self), data)
def insert_at_nth(self, index: int, data):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.insert_at_nth(-1, 666)
Traceback (most recent call last):
....
IndexError: list index out of range
>>> linked_list.insert_at_nth(1, 666)
Traceback (most recent call last):
....
IndexError: list index out of range
>>> linked_list.insert_at_nth(0, 2)
>>> linked_list.insert_at_nth(0, 1)
>>> linked_list.insert_at_nth(2, 4)
>>> linked_list.insert_at_nth(2, 3)
>>> str(linked_list)
'1->2->3->4'
>>> linked_list.insert_at_nth(5, 5)
Traceback (most recent call last):
....
IndexError: list index out of range
"""
if not 0 <= index <= len(self):
raise IndexError("list index out of range")
new_node = Node(data)
if self.head is None:
self.head = self.tail = new_node
elif index == 0:
self.head.previous = new_node
new_node.next = self.head
self.head = new_node
elif index == len(self):
self.tail.next = new_node
new_node.previous = self.tail
self.tail = new_node
else:
temp = self.head
for i in range(0, index):
temp = temp.next
temp.previous.next = new_node
new_node.previous = temp.previous
new_node.next = temp
temp.previous = new_node
def delete_head(self):
return self.delete_at_nth(0)
def delete_tail(self):
return self.delete_at_nth(len(self) - 1)
def delete_at_nth(self, index: int):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.delete_at_nth(0)
Traceback (most recent call last):
....
IndexError: list index out of range
>>> for i in range(0, 5):
... linked_list.insert_at_nth(i, i + 1)
>>> linked_list.delete_at_nth(0) == 1
True
>>> linked_list.delete_at_nth(3) == 5
True
>>> linked_list.delete_at_nth(1) == 3
True
>>> str(linked_list)
'2->4'
>>> linked_list.delete_at_nth(2)
Traceback (most recent call last):
....
IndexError: list index out of range
"""
if not 0 <= index <= len(self) - 1:
raise IndexError("list index out of range")
delete_node = self.head # default first node
if len(self) == 1:
self.head = self.tail = None
elif index == 0:
self.head = self.head.next
self.head.previous = None
elif index == len(self) - 1:
delete_node = self.tail
self.tail = self.tail.previous
self.tail.next = None
else:
temp = self.head
for i in range(0, index):
temp = temp.next
delete_node = temp
temp.next.previous = temp.previous
temp.previous.next = temp.next
return delete_node.data
def delete(self, data) -> str:
current = self.head
while current.data != data: # Find the position to delete
if current.next:
current = current.next
else: # We have reached the end an no value matches
return "No data matching given value"
if current == self.head:
self.delete_head()
elif current == self.tail:
self.delete_tail()
else: # Before: 1 <--> 2(current) <--> 3
current.previous.next = current.next # 1 --> 3
current.next.previous = current.previous # 1 <--> 3
return data
def is_empty(self):
"""
>>> linked_list = DoublyLinkedList()
>>> linked_list.is_empty()
True
>>> linked_list.insert_at_tail(1)
>>> linked_list.is_empty()
False
"""
return len(self) == 0
def test_doubly_linked_list() -> None:
"""
>>> test_doubly_linked_list()
"""
linked_list = DoublyLinkedList()
assert linked_list.is_empty() is True
assert str(linked_list) == ""
try:
linked_list.delete_head()
assert False # This should not happen.
except IndexError:
assert True # This should happen.
try:
linked_list.delete_tail()
assert False # This should not happen.
except IndexError:
assert True # This should happen.
for i in range(10):
assert len(linked_list) == i
linked_list.insert_at_nth(i, i + 1)
assert str(linked_list) == "->".join(str(i) for i in range(1, 11))
linked_list.insert_at_head(0)
linked_list.insert_at_tail(11)
assert str(linked_list) == "->".join(str(i) for i in range(0, 12))
assert linked_list.delete_head() == 0
assert linked_list.delete_at_nth(9) == 10
assert linked_list.delete_tail() == 11
assert len(linked_list) == 9
assert str(linked_list) == "->".join(str(i) for i in range(1, 10))
if __name__ == "__main__":
from doctest import testmod
testmod()
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
FP-GraphMiner - A Fast Frequent Pattern Mining Algorithm for Network Graphs
A novel Frequent Pattern Graph Mining algorithm, FP-GraphMiner, that compactly
represents a set of network graphs as a Frequent Pattern Graph (or FP-Graph).
This graph can be used to efficiently mine frequent subgraphs including maximal
frequent subgraphs and maximum common subgraphs.
URL: https://www.researchgate.net/publication/235255851
"""
# fmt: off
edge_array = [
['ab-e1', 'ac-e3', 'ad-e5', 'bc-e4', 'bd-e2', 'be-e6', 'bh-e12', 'cd-e2', 'ce-e4',
'de-e1', 'df-e8', 'dg-e5', 'dh-e10', 'ef-e3', 'eg-e2', 'fg-e6', 'gh-e6', 'hi-e3'],
['ab-e1', 'ac-e3', 'ad-e5', 'bc-e4', 'bd-e2', 'be-e6', 'cd-e2', 'de-e1', 'df-e8',
'ef-e3', 'eg-e2', 'fg-e6'],
['ab-e1', 'ac-e3', 'bc-e4', 'bd-e2', 'de-e1', 'df-e8', 'dg-e5', 'ef-e3', 'eg-e2',
'eh-e12', 'fg-e6', 'fh-e10', 'gh-e6'],
['ab-e1', 'ac-e3', 'bc-e4', 'bd-e2', 'bh-e12', 'cd-e2', 'df-e8', 'dh-e10'],
['ab-e1', 'ac-e3', 'ad-e5', 'bc-e4', 'bd-e2', 'cd-e2', 'ce-e4', 'de-e1', 'df-e8',
'dg-e5', 'ef-e3', 'eg-e2', 'fg-e6']
]
# fmt: on
def get_distinct_edge(edge_array):
"""
Return Distinct edges from edge array of multiple graphs
>>> sorted(get_distinct_edge(edge_array))
['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h']
"""
distinct_edge = set()
for row in edge_array:
for item in row:
distinct_edge.add(item[0])
return list(distinct_edge)
def get_bitcode(edge_array, distinct_edge):
"""
Return bitcode of distinct_edge
"""
bitcode = ["0"] * len(edge_array)
for i, row in enumerate(edge_array):
for item in row:
if distinct_edge in item[0]:
bitcode[i] = "1"
break
return "".join(bitcode)
def get_frequency_table(edge_array):
"""
Returns Frequency Table
"""
distinct_edge = get_distinct_edge(edge_array)
frequency_table = dict()
for item in distinct_edge:
bit = get_bitcode(edge_array, item)
# print('bit',bit)
# bt=''.join(bit)
s = bit.count("1")
frequency_table[item] = [s, bit]
# Store [Distinct edge, WT(Bitcode), Bitcode] in descending order
sorted_frequency_table = [
[k, v[0], v[1]]
for k, v in sorted(frequency_table.items(), key=lambda v: v[1][0], reverse=True)
]
return sorted_frequency_table
def get_nodes(frequency_table):
"""
Returns nodes
format nodes={bitcode:edges that represent the bitcode}
>>> get_nodes([['ab', 5, '11111'], ['ac', 5, '11111'], ['df', 5, '11111'],
... ['bd', 5, '11111'], ['bc', 5, '11111']])
{'11111': ['ab', 'ac', 'df', 'bd', 'bc']}
"""
nodes = {}
for i, item in enumerate(frequency_table):
nodes.setdefault(item[2], []).append(item[0])
return nodes
def get_cluster(nodes):
"""
Returns cluster
format cluster:{WT(bitcode):nodes with same WT}
"""
cluster = {}
for key, value in nodes.items():
cluster.setdefault(key.count("1"), {})[key] = value
return cluster
def get_support(cluster):
"""
Returns support
>>> get_support({5: {'11111': ['ab', 'ac', 'df', 'bd', 'bc']},
... 4: {'11101': ['ef', 'eg', 'de', 'fg'], '11011': ['cd']},
... 3: {'11001': ['ad'], '10101': ['dg']},
... 2: {'10010': ['dh', 'bh'], '11000': ['be'], '10100': ['gh'],
... '10001': ['ce']},
... 1: {'00100': ['fh', 'eh'], '10000': ['hi']}})
[100.0, 80.0, 60.0, 40.0, 20.0]
"""
return [i * 100 / len(cluster) for i in cluster]
def print_all() -> None:
print("\nNodes\n")
for key, value in nodes.items():
print(key, value)
print("\nSupport\n")
print(support)
print("\n Cluster \n")
for key, value in sorted(cluster.items(), reverse=True):
print(key, value)
print("\n Graph\n")
for key, value in graph.items():
print(key, value)
print("\n Edge List of Frequent subgraphs \n")
for edge_list in freq_subgraph_edge_list:
print(edge_list)
def create_edge(nodes, graph, cluster, c1):
"""
create edge between the nodes
"""
for i in cluster[c1].keys():
count = 0
c2 = c1 + 1
while c2 < max(cluster.keys()):
for j in cluster[c2].keys():
"""
creates edge only if the condition satisfies
"""
if int(i, 2) & int(j, 2) == int(i, 2):
if tuple(nodes[i]) in graph:
graph[tuple(nodes[i])].append(nodes[j])
else:
graph[tuple(nodes[i])] = [nodes[j]]
count += 1
if count == 0:
c2 = c2 + 1
else:
break
def construct_graph(cluster, nodes):
X = cluster[max(cluster.keys())]
cluster[max(cluster.keys()) + 1] = "Header"
graph = {}
for i in X:
if tuple(["Header"]) in graph:
graph[tuple(["Header"])].append(X[i])
else:
graph[tuple(["Header"])] = [X[i]]
for i in X:
graph[tuple(X[i])] = [["Header"]]
i = 1
while i < max(cluster) - 1:
create_edge(nodes, graph, cluster, i)
i = i + 1
return graph
def myDFS(graph, start, end, path=[]):
"""
find different DFS walk from given node to Header node
"""
path = path + [start]
if start == end:
paths.append(path)
for node in graph[start]:
if tuple(node) not in path:
myDFS(graph, tuple(node), end, path)
def find_freq_subgraph_given_support(s, cluster, graph):
"""
find edges of multiple frequent subgraphs
"""
k = int(s / 100 * (len(cluster) - 1))
for i in cluster[k].keys():
myDFS(graph, tuple(cluster[k][i]), tuple(["Header"]))
def freq_subgraphs_edge_list(paths):
"""
returns Edge list for frequent subgraphs
"""
freq_sub_EL = []
for edges in paths:
EL = []
for j in range(len(edges) - 1):
temp = list(edges[j])
for e in temp:
edge = (e[0], e[1])
EL.append(edge)
freq_sub_EL.append(EL)
return freq_sub_EL
def preprocess(edge_array):
"""
Preprocess the edge array
>>> preprocess([['ab-e1', 'ac-e3', 'ad-e5', 'bc-e4', 'bd-e2', 'be-e6', 'bh-e12',
... 'cd-e2', 'ce-e4', 'de-e1', 'df-e8', 'dg-e5', 'dh-e10', 'ef-e3',
... 'eg-e2', 'fg-e6', 'gh-e6', 'hi-e3']])
"""
for i in range(len(edge_array)):
for j in range(len(edge_array[i])):
t = edge_array[i][j].split("-")
edge_array[i][j] = t
if __name__ == "__main__":
preprocess(edge_array)
frequency_table = get_frequency_table(edge_array)
nodes = get_nodes(frequency_table)
cluster = get_cluster(nodes)
support = get_support(cluster)
graph = construct_graph(cluster, nodes)
find_freq_subgraph_given_support(60, cluster, graph)
paths = []
freq_subgraph_edge_list = freq_subgraphs_edge_list(paths)
print_all()
| """
FP-GraphMiner - A Fast Frequent Pattern Mining Algorithm for Network Graphs
A novel Frequent Pattern Graph Mining algorithm, FP-GraphMiner, that compactly
represents a set of network graphs as a Frequent Pattern Graph (or FP-Graph).
This graph can be used to efficiently mine frequent subgraphs including maximal
frequent subgraphs and maximum common subgraphs.
URL: https://www.researchgate.net/publication/235255851
"""
# fmt: off
edge_array = [
['ab-e1', 'ac-e3', 'ad-e5', 'bc-e4', 'bd-e2', 'be-e6', 'bh-e12', 'cd-e2', 'ce-e4',
'de-e1', 'df-e8', 'dg-e5', 'dh-e10', 'ef-e3', 'eg-e2', 'fg-e6', 'gh-e6', 'hi-e3'],
['ab-e1', 'ac-e3', 'ad-e5', 'bc-e4', 'bd-e2', 'be-e6', 'cd-e2', 'de-e1', 'df-e8',
'ef-e3', 'eg-e2', 'fg-e6'],
['ab-e1', 'ac-e3', 'bc-e4', 'bd-e2', 'de-e1', 'df-e8', 'dg-e5', 'ef-e3', 'eg-e2',
'eh-e12', 'fg-e6', 'fh-e10', 'gh-e6'],
['ab-e1', 'ac-e3', 'bc-e4', 'bd-e2', 'bh-e12', 'cd-e2', 'df-e8', 'dh-e10'],
['ab-e1', 'ac-e3', 'ad-e5', 'bc-e4', 'bd-e2', 'cd-e2', 'ce-e4', 'de-e1', 'df-e8',
'dg-e5', 'ef-e3', 'eg-e2', 'fg-e6']
]
# fmt: on
def get_distinct_edge(edge_array):
"""
Return Distinct edges from edge array of multiple graphs
>>> sorted(get_distinct_edge(edge_array))
['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h']
"""
distinct_edge = set()
for row in edge_array:
for item in row:
distinct_edge.add(item[0])
return list(distinct_edge)
def get_bitcode(edge_array, distinct_edge):
"""
Return bitcode of distinct_edge
"""
bitcode = ["0"] * len(edge_array)
for i, row in enumerate(edge_array):
for item in row:
if distinct_edge in item[0]:
bitcode[i] = "1"
break
return "".join(bitcode)
def get_frequency_table(edge_array):
"""
Returns Frequency Table
"""
distinct_edge = get_distinct_edge(edge_array)
frequency_table = dict()
for item in distinct_edge:
bit = get_bitcode(edge_array, item)
# print('bit',bit)
# bt=''.join(bit)
s = bit.count("1")
frequency_table[item] = [s, bit]
# Store [Distinct edge, WT(Bitcode), Bitcode] in descending order
sorted_frequency_table = [
[k, v[0], v[1]]
for k, v in sorted(frequency_table.items(), key=lambda v: v[1][0], reverse=True)
]
return sorted_frequency_table
def get_nodes(frequency_table):
"""
Returns nodes
format nodes={bitcode:edges that represent the bitcode}
>>> get_nodes([['ab', 5, '11111'], ['ac', 5, '11111'], ['df', 5, '11111'],
... ['bd', 5, '11111'], ['bc', 5, '11111']])
{'11111': ['ab', 'ac', 'df', 'bd', 'bc']}
"""
nodes = {}
for i, item in enumerate(frequency_table):
nodes.setdefault(item[2], []).append(item[0])
return nodes
def get_cluster(nodes):
"""
Returns cluster
format cluster:{WT(bitcode):nodes with same WT}
"""
cluster = {}
for key, value in nodes.items():
cluster.setdefault(key.count("1"), {})[key] = value
return cluster
def get_support(cluster):
"""
Returns support
>>> get_support({5: {'11111': ['ab', 'ac', 'df', 'bd', 'bc']},
... 4: {'11101': ['ef', 'eg', 'de', 'fg'], '11011': ['cd']},
... 3: {'11001': ['ad'], '10101': ['dg']},
... 2: {'10010': ['dh', 'bh'], '11000': ['be'], '10100': ['gh'],
... '10001': ['ce']},
... 1: {'00100': ['fh', 'eh'], '10000': ['hi']}})
[100.0, 80.0, 60.0, 40.0, 20.0]
"""
return [i * 100 / len(cluster) for i in cluster]
def print_all() -> None:
print("\nNodes\n")
for key, value in nodes.items():
print(key, value)
print("\nSupport\n")
print(support)
print("\n Cluster \n")
for key, value in sorted(cluster.items(), reverse=True):
print(key, value)
print("\n Graph\n")
for key, value in graph.items():
print(key, value)
print("\n Edge List of Frequent subgraphs \n")
for edge_list in freq_subgraph_edge_list:
print(edge_list)
def create_edge(nodes, graph, cluster, c1):
"""
create edge between the nodes
"""
for i in cluster[c1].keys():
count = 0
c2 = c1 + 1
while c2 < max(cluster.keys()):
for j in cluster[c2].keys():
"""
creates edge only if the condition satisfies
"""
if int(i, 2) & int(j, 2) == int(i, 2):
if tuple(nodes[i]) in graph:
graph[tuple(nodes[i])].append(nodes[j])
else:
graph[tuple(nodes[i])] = [nodes[j]]
count += 1
if count == 0:
c2 = c2 + 1
else:
break
def construct_graph(cluster, nodes):
X = cluster[max(cluster.keys())]
cluster[max(cluster.keys()) + 1] = "Header"
graph = {}
for i in X:
if tuple(["Header"]) in graph:
graph[tuple(["Header"])].append(X[i])
else:
graph[tuple(["Header"])] = [X[i]]
for i in X:
graph[tuple(X[i])] = [["Header"]]
i = 1
while i < max(cluster) - 1:
create_edge(nodes, graph, cluster, i)
i = i + 1
return graph
def myDFS(graph, start, end, path=[]):
"""
find different DFS walk from given node to Header node
"""
path = path + [start]
if start == end:
paths.append(path)
for node in graph[start]:
if tuple(node) not in path:
myDFS(graph, tuple(node), end, path)
def find_freq_subgraph_given_support(s, cluster, graph):
"""
find edges of multiple frequent subgraphs
"""
k = int(s / 100 * (len(cluster) - 1))
for i in cluster[k].keys():
myDFS(graph, tuple(cluster[k][i]), tuple(["Header"]))
def freq_subgraphs_edge_list(paths):
"""
returns Edge list for frequent subgraphs
"""
freq_sub_EL = []
for edges in paths:
EL = []
for j in range(len(edges) - 1):
temp = list(edges[j])
for e in temp:
edge = (e[0], e[1])
EL.append(edge)
freq_sub_EL.append(EL)
return freq_sub_EL
def preprocess(edge_array):
"""
Preprocess the edge array
>>> preprocess([['ab-e1', 'ac-e3', 'ad-e5', 'bc-e4', 'bd-e2', 'be-e6', 'bh-e12',
... 'cd-e2', 'ce-e4', 'de-e1', 'df-e8', 'dg-e5', 'dh-e10', 'ef-e3',
... 'eg-e2', 'fg-e6', 'gh-e6', 'hi-e3']])
"""
for i in range(len(edge_array)):
for j in range(len(edge_array[i])):
t = edge_array[i][j].split("-")
edge_array[i][j] = t
if __name__ == "__main__":
preprocess(edge_array)
frequency_table = get_frequency_table(edge_array)
nodes = get_nodes(frequency_table)
cluster = get_cluster(nodes)
support = get_support(cluster)
graph = construct_graph(cluster, nodes)
find_freq_subgraph_given_support(60, cluster, graph)
paths = []
freq_subgraph_edge_list = freq_subgraphs_edge_list(paths)
print_all()
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from sklearn import svm
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
# different functions implementing different types of SVM's
def NuSVC(train_x, train_y):
svc_NuSVC = svm.NuSVC()
svc_NuSVC.fit(train_x, train_y)
return svc_NuSVC
def Linearsvc(train_x, train_y):
svc_linear = svm.LinearSVC(tol=10e-2)
svc_linear.fit(train_x, train_y)
return svc_linear
def SVC(train_x, train_y):
# svm.SVC(C=1.0, kernel='rbf', degree=3, gamma=0.0, coef0=0.0, shrinking=True,
# probability=False,tol=0.001, cache_size=200, class_weight=None, verbose=False,
# max_iter=1000, random_state=None)
# various parameters like "kernel","gamma","C" can effectively tuned for a given
# machine learning model.
SVC = svm.SVC(gamma="auto")
SVC.fit(train_x, train_y)
return SVC
def test(X_new):
"""
3 test cases to be passed
an array containing the sepal length (cm), sepal width (cm), petal length (cm),
petal width (cm) based on which the target name will be predicted
>>> test([1,2,1,4])
'virginica'
>>> test([5, 2, 4, 1])
'versicolor'
>>> test([6,3,4,1])
'versicolor'
"""
iris = load_iris()
# splitting the dataset to test and train
train_x, test_x, train_y, test_y = train_test_split(
iris["data"], iris["target"], random_state=4
)
# any of the 3 types of SVM can be used
# current_model=SVC(train_x, train_y)
# current_model=NuSVC(train_x, train_y)
current_model = Linearsvc(train_x, train_y)
prediction = current_model.predict([X_new])
return iris["target_names"][prediction][0]
if __name__ == "__main__":
import doctest
doctest.testmod()
| from sklearn import svm
from sklearn.datasets import load_iris
from sklearn.model_selection import train_test_split
# different functions implementing different types of SVM's
def NuSVC(train_x, train_y):
svc_NuSVC = svm.NuSVC()
svc_NuSVC.fit(train_x, train_y)
return svc_NuSVC
def Linearsvc(train_x, train_y):
svc_linear = svm.LinearSVC(tol=10e-2)
svc_linear.fit(train_x, train_y)
return svc_linear
def SVC(train_x, train_y):
# svm.SVC(C=1.0, kernel='rbf', degree=3, gamma=0.0, coef0=0.0, shrinking=True,
# probability=False,tol=0.001, cache_size=200, class_weight=None, verbose=False,
# max_iter=1000, random_state=None)
# various parameters like "kernel","gamma","C" can effectively tuned for a given
# machine learning model.
SVC = svm.SVC(gamma="auto")
SVC.fit(train_x, train_y)
return SVC
def test(X_new):
"""
3 test cases to be passed
an array containing the sepal length (cm), sepal width (cm), petal length (cm),
petal width (cm) based on which the target name will be predicted
>>> test([1,2,1,4])
'virginica'
>>> test([5, 2, 4, 1])
'versicolor'
>>> test([6,3,4,1])
'versicolor'
"""
iris = load_iris()
# splitting the dataset to test and train
train_x, test_x, train_y, test_y = train_test_split(
iris["data"], iris["target"], random_state=4
)
# any of the 3 types of SVM can be used
# current_model=SVC(train_x, train_y)
# current_model=NuSVC(train_x, train_y)
current_model = Linearsvc(train_x, train_y)
prediction = current_model.predict([X_new])
return iris["target_names"][prediction][0]
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| import numpy as np
def power_iteration(
input_matrix: np.array, vector: np.array, error_tol=1e-12, max_iterations=100
) -> [float, np.array]:
"""
Power Iteration.
Find the largest eignevalue and corresponding eigenvector
of matrix input_matrix given a random vector in the same space.
Will work so long as vector has component of largest eigenvector.
input_matrix must be symmetric.
Input
input_matrix: input matrix whose largest eigenvalue we will find.
Numpy array. np.shape(input_matrix) == (N,N).
vector: random initial vector in same space as matrix.
Numpy array. np.shape(vector) == (N,) or (N,1)
Output
largest_eigenvalue: largest eigenvalue of the matrix input_matrix.
Float. Scalar.
largest_eigenvector: eigenvector corresponding to largest_eigenvalue.
Numpy array. np.shape(largest_eigenvector) == (N,) or (N,1).
>>> import numpy as np
>>> input_matrix = np.array([
... [41, 4, 20],
... [ 4, 26, 30],
... [20, 30, 50]
... ])
>>> vector = np.array([41,4,20])
>>> power_iteration(input_matrix,vector)
(79.66086378788381, array([0.44472726, 0.46209842, 0.76725662]))
"""
# Ensure matrix is square.
assert np.shape(input_matrix)[0] == np.shape(input_matrix)[1]
# Ensure proper dimensionality.
assert np.shape(input_matrix)[0] == np.shape(vector)[0]
# Set convergence to False. Will define convergence when we exceed max_iterations
# or when we have small changes from one iteration to next.
convergence = False
lamda_previous = 0
iterations = 0
error = 1e12
while not convergence:
# Multiple matrix by the vector.
w = np.dot(input_matrix, vector)
# Normalize the resulting output vector.
vector = w / np.linalg.norm(w)
# Find rayleigh quotient
# (faster than usual b/c we know vector is normalized already)
lamda = np.dot(vector.T, np.dot(input_matrix, vector))
# Check convergence.
error = np.abs(lamda - lamda_previous) / lamda
iterations += 1
if error <= error_tol or iterations >= max_iterations:
convergence = True
lamda_previous = lamda
return lamda, vector
def test_power_iteration() -> None:
"""
>>> test_power_iteration() # self running tests
"""
# Our implementation.
input_matrix = np.array([[41, 4, 20], [4, 26, 30], [20, 30, 50]])
vector = np.array([41, 4, 20])
eigen_value, eigen_vector = power_iteration(input_matrix, vector)
# Numpy implementation.
# Get eigen values and eigen vectors using built in numpy
# eigh (eigh used for symmetric or hermetian matrices).
eigen_values, eigen_vectors = np.linalg.eigh(input_matrix)
# Last eigen value is the maximum one.
eigen_value_max = eigen_values[-1]
# Last column in this matrix is eigen vector corresponding to largest eigen value.
eigen_vector_max = eigen_vectors[:, -1]
# Check our implementation and numpy gives close answers.
assert np.abs(eigen_value - eigen_value_max) <= 1e-6
# Take absolute values element wise of each eigenvector.
# as they are only unique to a minus sign.
assert np.linalg.norm(np.abs(eigen_vector) - np.abs(eigen_vector_max)) <= 1e-6
if __name__ == "__main__":
import doctest
doctest.testmod()
test_power_iteration()
| import numpy as np
def power_iteration(
input_matrix: np.array, vector: np.array, error_tol=1e-12, max_iterations=100
) -> [float, np.array]:
"""
Power Iteration.
Find the largest eignevalue and corresponding eigenvector
of matrix input_matrix given a random vector in the same space.
Will work so long as vector has component of largest eigenvector.
input_matrix must be symmetric.
Input
input_matrix: input matrix whose largest eigenvalue we will find.
Numpy array. np.shape(input_matrix) == (N,N).
vector: random initial vector in same space as matrix.
Numpy array. np.shape(vector) == (N,) or (N,1)
Output
largest_eigenvalue: largest eigenvalue of the matrix input_matrix.
Float. Scalar.
largest_eigenvector: eigenvector corresponding to largest_eigenvalue.
Numpy array. np.shape(largest_eigenvector) == (N,) or (N,1).
>>> import numpy as np
>>> input_matrix = np.array([
... [41, 4, 20],
... [ 4, 26, 30],
... [20, 30, 50]
... ])
>>> vector = np.array([41,4,20])
>>> power_iteration(input_matrix,vector)
(79.66086378788381, array([0.44472726, 0.46209842, 0.76725662]))
"""
# Ensure matrix is square.
assert np.shape(input_matrix)[0] == np.shape(input_matrix)[1]
# Ensure proper dimensionality.
assert np.shape(input_matrix)[0] == np.shape(vector)[0]
# Set convergence to False. Will define convergence when we exceed max_iterations
# or when we have small changes from one iteration to next.
convergence = False
lamda_previous = 0
iterations = 0
error = 1e12
while not convergence:
# Multiple matrix by the vector.
w = np.dot(input_matrix, vector)
# Normalize the resulting output vector.
vector = w / np.linalg.norm(w)
# Find rayleigh quotient
# (faster than usual b/c we know vector is normalized already)
lamda = np.dot(vector.T, np.dot(input_matrix, vector))
# Check convergence.
error = np.abs(lamda - lamda_previous) / lamda
iterations += 1
if error <= error_tol or iterations >= max_iterations:
convergence = True
lamda_previous = lamda
return lamda, vector
def test_power_iteration() -> None:
"""
>>> test_power_iteration() # self running tests
"""
# Our implementation.
input_matrix = np.array([[41, 4, 20], [4, 26, 30], [20, 30, 50]])
vector = np.array([41, 4, 20])
eigen_value, eigen_vector = power_iteration(input_matrix, vector)
# Numpy implementation.
# Get eigen values and eigen vectors using built in numpy
# eigh (eigh used for symmetric or hermetian matrices).
eigen_values, eigen_vectors = np.linalg.eigh(input_matrix)
# Last eigen value is the maximum one.
eigen_value_max = eigen_values[-1]
# Last column in this matrix is eigen vector corresponding to largest eigen value.
eigen_vector_max = eigen_vectors[:, -1]
# Check our implementation and numpy gives close answers.
assert np.abs(eigen_value - eigen_value_max) <= 1e-6
# Take absolute values element wise of each eigenvector.
# as they are only unique to a minus sign.
assert np.linalg.norm(np.abs(eigen_vector) - np.abs(eigen_vector_max)) <= 1e-6
if __name__ == "__main__":
import doctest
doctest.testmod()
test_power_iteration()
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| alphabets = [chr(i) for i in range(32, 126)]
gear_one = [i for i in range(len(alphabets))]
gear_two = [i for i in range(len(alphabets))]
gear_three = [i for i in range(len(alphabets))]
reflector = [i for i in reversed(range(len(alphabets)))]
code = []
gear_one_pos = gear_two_pos = gear_three_pos = 0
def rotator():
global gear_one_pos
global gear_two_pos
global gear_three_pos
i = gear_one[0]
gear_one.append(i)
del gear_one[0]
gear_one_pos += 1
if gear_one_pos % int(len(alphabets)) == 0:
i = gear_two[0]
gear_two.append(i)
del gear_two[0]
gear_two_pos += 1
if gear_two_pos % int(len(alphabets)) == 0:
i = gear_three[0]
gear_three.append(i)
del gear_three[0]
gear_three_pos += 1
def engine(input_character):
target = alphabets.index(input_character)
target = gear_one[target]
target = gear_two[target]
target = gear_three[target]
target = reflector[target]
target = gear_three.index(target)
target = gear_two.index(target)
target = gear_one.index(target)
code.append(alphabets[target])
rotator()
if __name__ == "__main__":
decode = input("Type your message:\n")
decode = list(decode)
while True:
try:
token = int(input("Please set token:(must be only digits)\n"))
break
except Exception as error:
print(error)
for i in range(token):
rotator()
for i in decode:
engine(i)
print("\n" + "".join(code))
print(
f"\nYour Token is {token} please write it down.\nIf you want to decode "
f"this message again you should input same digits as token!"
)
| alphabets = [chr(i) for i in range(32, 126)]
gear_one = [i for i in range(len(alphabets))]
gear_two = [i for i in range(len(alphabets))]
gear_three = [i for i in range(len(alphabets))]
reflector = [i for i in reversed(range(len(alphabets)))]
code = []
gear_one_pos = gear_two_pos = gear_three_pos = 0
def rotator():
global gear_one_pos
global gear_two_pos
global gear_three_pos
i = gear_one[0]
gear_one.append(i)
del gear_one[0]
gear_one_pos += 1
if gear_one_pos % int(len(alphabets)) == 0:
i = gear_two[0]
gear_two.append(i)
del gear_two[0]
gear_two_pos += 1
if gear_two_pos % int(len(alphabets)) == 0:
i = gear_three[0]
gear_three.append(i)
del gear_three[0]
gear_three_pos += 1
def engine(input_character):
target = alphabets.index(input_character)
target = gear_one[target]
target = gear_two[target]
target = gear_three[target]
target = reflector[target]
target = gear_three.index(target)
target = gear_two.index(target)
target = gear_one.index(target)
code.append(alphabets[target])
rotator()
if __name__ == "__main__":
decode = input("Type your message:\n")
decode = list(decode)
while True:
try:
token = int(input("Please set token:(must be only digits)\n"))
break
except Exception as error:
print(error)
for i in range(token):
rotator()
for i in decode:
engine(i)
print("\n" + "".join(code))
print(
f"\nYour Token is {token} please write it down.\nIf you want to decode "
f"this message again you should input same digits as token!"
)
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Prim's (also known as Jarník's) algorithm is a greedy algorithm that finds a minimum
spanning tree for a weighted undirected graph. This means it finds a subset of the
edges that forms a tree that includes every vertex, where the total weight of all the
edges in the tree is minimized. The algorithm operates by building this tree one vertex
at a time, from an arbitrary starting vertex, at each step adding the cheapest possible
connection from the tree to another vertex.
"""
from sys import maxsize
from typing import Dict, Optional, Tuple, Union
def get_parent_position(position: int) -> int:
"""
heap helper function get the position of the parent of the current node
>>> get_parent_position(1)
0
>>> get_parent_position(2)
0
"""
return (position - 1) // 2
def get_child_left_position(position: int) -> int:
"""
heap helper function get the position of the left child of the current node
>>> get_child_left_position(0)
1
"""
return (2 * position) + 1
def get_child_right_position(position: int) -> int:
"""
heap helper function get the position of the right child of the current node
>>> get_child_right_position(0)
2
"""
return (2 * position) + 2
class MinPriorityQueue:
"""
Minimum Priority Queue Class
Functions:
is_empty: function to check if the priority queue is empty
push: function to add an element with given priority to the queue
extract_min: function to remove and return the element with lowest weight (highest
priority)
update_key: function to update the weight of the given key
_bubble_up: helper function to place a node at the proper position (upward
movement)
_bubble_down: helper function to place a node at the proper position (downward
movement)
_swap_nodes: helper function to swap the nodes at the given positions
>>> queue = MinPriorityQueue()
>>> queue.push(1, 1000)
>>> queue.push(2, 100)
>>> queue.push(3, 4000)
>>> queue.push(4, 3000)
>>> print(queue.extract_min())
2
>>> queue.update_key(4, 50)
>>> print(queue.extract_min())
4
>>> print(queue.extract_min())
1
>>> print(queue.extract_min())
3
"""
def __init__(self) -> None:
self.heap = []
self.position_map = {}
self.elements = 0
def __len__(self) -> int:
return self.elements
def __repr__(self) -> str:
return str(self.heap)
def is_empty(self) -> bool:
# Check if the priority queue is empty
return self.elements == 0
def push(self, elem: Union[int, str], weight: int) -> None:
# Add an element with given priority to the queue
self.heap.append((elem, weight))
self.position_map[elem] = self.elements
self.elements += 1
self._bubble_up(elem)
def extract_min(self) -> Union[int, str]:
# Remove and return the element with lowest weight (highest priority)
if self.elements > 1:
self._swap_nodes(0, self.elements - 1)
elem, _ = self.heap.pop()
del self.position_map[elem]
self.elements -= 1
if self.elements > 0:
bubble_down_elem, _ = self.heap[0]
self._bubble_down(bubble_down_elem)
return elem
def update_key(self, elem: Union[int, str], weight: int) -> None:
# Update the weight of the given key
position = self.position_map[elem]
self.heap[position] = (elem, weight)
if position > 0:
parent_position = get_parent_position(position)
_, parent_weight = self.heap[parent_position]
if parent_weight > weight:
self._bubble_up(elem)
else:
self._bubble_down(elem)
else:
self._bubble_down(elem)
def _bubble_up(self, elem: Union[int, str]) -> None:
# Place a node at the proper position (upward movement) [to be used internally
# only]
curr_pos = self.position_map[elem]
if curr_pos == 0:
return
parent_position = get_parent_position(curr_pos)
_, weight = self.heap[curr_pos]
_, parent_weight = self.heap[parent_position]
if parent_weight > weight:
self._swap_nodes(parent_position, curr_pos)
return self._bubble_up(elem)
return
def _bubble_down(self, elem: Union[int, str]) -> None:
# Place a node at the proper position (downward movement) [to be used
# internally only]
curr_pos = self.position_map[elem]
_, weight = self.heap[curr_pos]
child_left_position = get_child_left_position(curr_pos)
child_right_position = get_child_right_position(curr_pos)
if child_left_position < self.elements and child_right_position < self.elements:
_, child_left_weight = self.heap[child_left_position]
_, child_right_weight = self.heap[child_right_position]
if child_right_weight < child_left_weight:
if child_right_weight < weight:
self._swap_nodes(child_right_position, curr_pos)
return self._bubble_down(elem)
if child_left_position < self.elements:
_, child_left_weight = self.heap[child_left_position]
if child_left_weight < weight:
self._swap_nodes(child_left_position, curr_pos)
return self._bubble_down(elem)
else:
return
if child_right_position < self.elements:
_, child_right_weight = self.heap[child_right_position]
if child_right_weight < weight:
self._swap_nodes(child_right_position, curr_pos)
return self._bubble_down(elem)
else:
return
def _swap_nodes(self, node1_pos: int, node2_pos: int) -> None:
# Swap the nodes at the given positions
node1_elem = self.heap[node1_pos][0]
node2_elem = self.heap[node2_pos][0]
self.heap[node1_pos], self.heap[node2_pos] = (
self.heap[node2_pos],
self.heap[node1_pos],
)
self.position_map[node1_elem] = node2_pos
self.position_map[node2_elem] = node1_pos
class GraphUndirectedWeighted:
"""
Graph Undirected Weighted Class
Functions:
add_node: function to add a node in the graph
add_edge: function to add an edge between 2 nodes in the graph
"""
def __init__(self) -> None:
self.connections = {}
self.nodes = 0
def __repr__(self) -> str:
return str(self.connections)
def __len__(self) -> int:
return self.nodes
def add_node(self, node: Union[int, str]) -> None:
# Add a node in the graph if it is not in the graph
if node not in self.connections:
self.connections[node] = {}
self.nodes += 1
def add_edge(
self, node1: Union[int, str], node2: Union[int, str], weight: int
) -> None:
# Add an edge between 2 nodes in the graph
self.add_node(node1)
self.add_node(node2)
self.connections[node1][node2] = weight
self.connections[node2][node1] = weight
def prims_algo(
graph: GraphUndirectedWeighted,
) -> Tuple[Dict[str, int], Dict[str, Optional[str]]]:
"""
>>> graph = GraphUndirectedWeighted()
>>> graph.add_edge("a", "b", 3)
>>> graph.add_edge("b", "c", 10)
>>> graph.add_edge("c", "d", 5)
>>> graph.add_edge("a", "c", 15)
>>> graph.add_edge("b", "d", 100)
>>> dist, parent = prims_algo(graph)
>>> abs(dist["a"] - dist["b"])
3
>>> abs(dist["d"] - dist["b"])
15
>>> abs(dist["a"] - dist["c"])
13
"""
# prim's algorithm for minimum spanning tree
dist = {node: maxsize for node in graph.connections}
parent = {node: None for node in graph.connections}
priority_queue = MinPriorityQueue()
[priority_queue.push(node, weight) for node, weight in dist.items()]
if priority_queue.is_empty():
return dist, parent
# initialization
node = priority_queue.extract_min()
dist[node] = 0
for neighbour in graph.connections[node]:
if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
dist[neighbour] = dist[node] + graph.connections[node][neighbour]
priority_queue.update_key(neighbour, dist[neighbour])
parent[neighbour] = node
# running prim's algorithm
while not priority_queue.is_empty():
node = priority_queue.extract_min()
for neighbour in graph.connections[node]:
if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
dist[neighbour] = dist[node] + graph.connections[node][neighbour]
priority_queue.update_key(neighbour, dist[neighbour])
parent[neighbour] = node
return dist, parent
if __name__ == "__main__":
from doctest import testmod
testmod()
| """
Prim's (also known as Jarník's) algorithm is a greedy algorithm that finds a minimum
spanning tree for a weighted undirected graph. This means it finds a subset of the
edges that forms a tree that includes every vertex, where the total weight of all the
edges in the tree is minimized. The algorithm operates by building this tree one vertex
at a time, from an arbitrary starting vertex, at each step adding the cheapest possible
connection from the tree to another vertex.
"""
from sys import maxsize
from typing import Dict, Optional, Tuple, Union
def get_parent_position(position: int) -> int:
"""
heap helper function get the position of the parent of the current node
>>> get_parent_position(1)
0
>>> get_parent_position(2)
0
"""
return (position - 1) // 2
def get_child_left_position(position: int) -> int:
"""
heap helper function get the position of the left child of the current node
>>> get_child_left_position(0)
1
"""
return (2 * position) + 1
def get_child_right_position(position: int) -> int:
"""
heap helper function get the position of the right child of the current node
>>> get_child_right_position(0)
2
"""
return (2 * position) + 2
class MinPriorityQueue:
"""
Minimum Priority Queue Class
Functions:
is_empty: function to check if the priority queue is empty
push: function to add an element with given priority to the queue
extract_min: function to remove and return the element with lowest weight (highest
priority)
update_key: function to update the weight of the given key
_bubble_up: helper function to place a node at the proper position (upward
movement)
_bubble_down: helper function to place a node at the proper position (downward
movement)
_swap_nodes: helper function to swap the nodes at the given positions
>>> queue = MinPriorityQueue()
>>> queue.push(1, 1000)
>>> queue.push(2, 100)
>>> queue.push(3, 4000)
>>> queue.push(4, 3000)
>>> print(queue.extract_min())
2
>>> queue.update_key(4, 50)
>>> print(queue.extract_min())
4
>>> print(queue.extract_min())
1
>>> print(queue.extract_min())
3
"""
def __init__(self) -> None:
self.heap = []
self.position_map = {}
self.elements = 0
def __len__(self) -> int:
return self.elements
def __repr__(self) -> str:
return str(self.heap)
def is_empty(self) -> bool:
# Check if the priority queue is empty
return self.elements == 0
def push(self, elem: Union[int, str], weight: int) -> None:
# Add an element with given priority to the queue
self.heap.append((elem, weight))
self.position_map[elem] = self.elements
self.elements += 1
self._bubble_up(elem)
def extract_min(self) -> Union[int, str]:
# Remove and return the element with lowest weight (highest priority)
if self.elements > 1:
self._swap_nodes(0, self.elements - 1)
elem, _ = self.heap.pop()
del self.position_map[elem]
self.elements -= 1
if self.elements > 0:
bubble_down_elem, _ = self.heap[0]
self._bubble_down(bubble_down_elem)
return elem
def update_key(self, elem: Union[int, str], weight: int) -> None:
# Update the weight of the given key
position = self.position_map[elem]
self.heap[position] = (elem, weight)
if position > 0:
parent_position = get_parent_position(position)
_, parent_weight = self.heap[parent_position]
if parent_weight > weight:
self._bubble_up(elem)
else:
self._bubble_down(elem)
else:
self._bubble_down(elem)
def _bubble_up(self, elem: Union[int, str]) -> None:
# Place a node at the proper position (upward movement) [to be used internally
# only]
curr_pos = self.position_map[elem]
if curr_pos == 0:
return
parent_position = get_parent_position(curr_pos)
_, weight = self.heap[curr_pos]
_, parent_weight = self.heap[parent_position]
if parent_weight > weight:
self._swap_nodes(parent_position, curr_pos)
return self._bubble_up(elem)
return
def _bubble_down(self, elem: Union[int, str]) -> None:
# Place a node at the proper position (downward movement) [to be used
# internally only]
curr_pos = self.position_map[elem]
_, weight = self.heap[curr_pos]
child_left_position = get_child_left_position(curr_pos)
child_right_position = get_child_right_position(curr_pos)
if child_left_position < self.elements and child_right_position < self.elements:
_, child_left_weight = self.heap[child_left_position]
_, child_right_weight = self.heap[child_right_position]
if child_right_weight < child_left_weight:
if child_right_weight < weight:
self._swap_nodes(child_right_position, curr_pos)
return self._bubble_down(elem)
if child_left_position < self.elements:
_, child_left_weight = self.heap[child_left_position]
if child_left_weight < weight:
self._swap_nodes(child_left_position, curr_pos)
return self._bubble_down(elem)
else:
return
if child_right_position < self.elements:
_, child_right_weight = self.heap[child_right_position]
if child_right_weight < weight:
self._swap_nodes(child_right_position, curr_pos)
return self._bubble_down(elem)
else:
return
def _swap_nodes(self, node1_pos: int, node2_pos: int) -> None:
# Swap the nodes at the given positions
node1_elem = self.heap[node1_pos][0]
node2_elem = self.heap[node2_pos][0]
self.heap[node1_pos], self.heap[node2_pos] = (
self.heap[node2_pos],
self.heap[node1_pos],
)
self.position_map[node1_elem] = node2_pos
self.position_map[node2_elem] = node1_pos
class GraphUndirectedWeighted:
"""
Graph Undirected Weighted Class
Functions:
add_node: function to add a node in the graph
add_edge: function to add an edge between 2 nodes in the graph
"""
def __init__(self) -> None:
self.connections = {}
self.nodes = 0
def __repr__(self) -> str:
return str(self.connections)
def __len__(self) -> int:
return self.nodes
def add_node(self, node: Union[int, str]) -> None:
# Add a node in the graph if it is not in the graph
if node not in self.connections:
self.connections[node] = {}
self.nodes += 1
def add_edge(
self, node1: Union[int, str], node2: Union[int, str], weight: int
) -> None:
# Add an edge between 2 nodes in the graph
self.add_node(node1)
self.add_node(node2)
self.connections[node1][node2] = weight
self.connections[node2][node1] = weight
def prims_algo(
graph: GraphUndirectedWeighted,
) -> Tuple[Dict[str, int], Dict[str, Optional[str]]]:
"""
>>> graph = GraphUndirectedWeighted()
>>> graph.add_edge("a", "b", 3)
>>> graph.add_edge("b", "c", 10)
>>> graph.add_edge("c", "d", 5)
>>> graph.add_edge("a", "c", 15)
>>> graph.add_edge("b", "d", 100)
>>> dist, parent = prims_algo(graph)
>>> abs(dist["a"] - dist["b"])
3
>>> abs(dist["d"] - dist["b"])
15
>>> abs(dist["a"] - dist["c"])
13
"""
# prim's algorithm for minimum spanning tree
dist = {node: maxsize for node in graph.connections}
parent = {node: None for node in graph.connections}
priority_queue = MinPriorityQueue()
[priority_queue.push(node, weight) for node, weight in dist.items()]
if priority_queue.is_empty():
return dist, parent
# initialization
node = priority_queue.extract_min()
dist[node] = 0
for neighbour in graph.connections[node]:
if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
dist[neighbour] = dist[node] + graph.connections[node][neighbour]
priority_queue.update_key(neighbour, dist[neighbour])
parent[neighbour] = node
# running prim's algorithm
while not priority_queue.is_empty():
node = priority_queue.extract_min()
for neighbour in graph.connections[node]:
if dist[neighbour] > dist[node] + graph.connections[node][neighbour]:
dist[neighbour] = dist[node] + graph.connections[node][neighbour]
priority_queue.update_key(neighbour, dist[neighbour])
parent[neighbour] = node
return dist, parent
if __name__ == "__main__":
from doctest import testmod
testmod()
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| def factors_of_a_number(num: int) -> list:
"""
>>> factors_of_a_number(1)
[1]
>>> factors_of_a_number(5)
[1, 5]
>>> factors_of_a_number(24)
[1, 2, 3, 4, 6, 8, 12, 24]
>>> factors_of_a_number(-24)
[]
"""
return [i for i in range(1, num + 1) if num % i == 0]
if __name__ == "__main__":
num = int(input("Enter a number to find its factors: "))
factors = factors_of_a_number(num)
print(f"{num} has {len(factors)} factors: {', '.join(str(f) for f in factors)}")
| def factors_of_a_number(num: int) -> list:
"""
>>> factors_of_a_number(1)
[1]
>>> factors_of_a_number(5)
[1, 5]
>>> factors_of_a_number(24)
[1, 2, 3, 4, 6, 8, 12, 24]
>>> factors_of_a_number(-24)
[]
"""
return [i for i in range(1, num + 1) if num % i == 0]
if __name__ == "__main__":
num = int(input("Enter a number to find its factors: "))
factors = factors_of_a_number(num)
print(f"{num} has {len(factors)} factors: {', '.join(str(f) for f in factors)}")
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Champernowne's constant
Problem 40
An irrational decimal fraction is created by concatenating the positive
integers:
0.123456789101112131415161718192021...
It can be seen that the 12th digit of the fractional part is 1.
If dn represents the nth digit of the fractional part, find the value of the
following expression.
d1 × d10 × d100 × d1000 × d10000 × d100000 × d1000000
"""
def solution():
"""Returns
>>> solution()
210
"""
constant = []
i = 1
while len(constant) < 1e6:
constant.append(str(i))
i += 1
constant = "".join(constant)
return (
int(constant[0])
* int(constant[9])
* int(constant[99])
* int(constant[999])
* int(constant[9999])
* int(constant[99999])
* int(constant[999999])
)
if __name__ == "__main__":
print(solution())
| """
Champernowne's constant
Problem 40
An irrational decimal fraction is created by concatenating the positive
integers:
0.123456789101112131415161718192021...
It can be seen that the 12th digit of the fractional part is 1.
If dn represents the nth digit of the fractional part, find the value of the
following expression.
d1 × d10 × d100 × d1000 × d10000 × d100000 × d1000000
"""
def solution():
"""Returns
>>> solution()
210
"""
constant = []
i = 1
while len(constant) < 1e6:
constant.append(str(i))
i += 1
constant = "".join(constant)
return (
int(constant[0])
* int(constant[9])
* int(constant[99])
* int(constant[999])
* int(constant[9999])
* int(constant[99999])
* int(constant[999999])
)
if __name__ == "__main__":
print(solution())
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
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TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Given a sorted array of integers, return indices of the two numbers such
that they add up to a specific target using the two pointers technique.
You may assume that each input would have exactly one solution, and you
may not use the same element twice.
This is an alternative solution of the two-sum problem, which uses a
map to solve the problem. Hence can not solve the issue if there is a
constraint not use the same index twice. [1]
Example:
Given nums = [2, 7, 11, 15], target = 9,
Because nums[0] + nums[1] = 2 + 7 = 9,
return [0, 1].
[1]: https://github.com/TheAlgorithms/Python/blob/master/other/two_sum.py
"""
from __future__ import annotations
def two_pointer(nums: list[int], target: int) -> list[int]:
"""
>>> two_pointer([2, 7, 11, 15], 9)
[0, 1]
>>> two_pointer([2, 7, 11, 15], 17)
[0, 3]
>>> two_pointer([2, 7, 11, 15], 18)
[1, 2]
>>> two_pointer([2, 7, 11, 15], 26)
[2, 3]
>>> two_pointer([1, 3, 3], 6)
[1, 2]
>>> two_pointer([2, 7, 11, 15], 8)
[]
>>> two_pointer([3 * i for i in range(10)], 19)
[]
>>> two_pointer([1, 2, 3], 6)
[]
"""
i = 0
j = len(nums) - 1
while i < j:
if nums[i] + nums[j] == target:
return [i, j]
elif nums[i] + nums[j] < target:
i = i + 1
else:
j = j - 1
return []
if __name__ == "__main__":
import doctest
doctest.testmod()
print(f"{two_pointer([2, 7, 11, 15], 9) = }")
| """
Given a sorted array of integers, return indices of the two numbers such
that they add up to a specific target using the two pointers technique.
You may assume that each input would have exactly one solution, and you
may not use the same element twice.
This is an alternative solution of the two-sum problem, which uses a
map to solve the problem. Hence can not solve the issue if there is a
constraint not use the same index twice. [1]
Example:
Given nums = [2, 7, 11, 15], target = 9,
Because nums[0] + nums[1] = 2 + 7 = 9,
return [0, 1].
[1]: https://github.com/TheAlgorithms/Python/blob/master/other/two_sum.py
"""
from __future__ import annotations
def two_pointer(nums: list[int], target: int) -> list[int]:
"""
>>> two_pointer([2, 7, 11, 15], 9)
[0, 1]
>>> two_pointer([2, 7, 11, 15], 17)
[0, 3]
>>> two_pointer([2, 7, 11, 15], 18)
[1, 2]
>>> two_pointer([2, 7, 11, 15], 26)
[2, 3]
>>> two_pointer([1, 3, 3], 6)
[1, 2]
>>> two_pointer([2, 7, 11, 15], 8)
[]
>>> two_pointer([3 * i for i in range(10)], 19)
[]
>>> two_pointer([1, 2, 3], 6)
[]
"""
i = 0
j = len(nums) - 1
while i < j:
if nums[i] + nums[j] == target:
return [i, j]
elif nums[i] + nums[j] < target:
i = i + 1
else:
j = j - 1
return []
if __name__ == "__main__":
import doctest
doctest.testmod()
print(f"{two_pointer([2, 7, 11, 15], 9) = }")
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Just to check
"""
def add(a, b):
"""
>>> add(2, 2)
4
>>> add(2, -2)
0
"""
return a + b
if __name__ == "__main__":
a = 5
b = 6
print(f"The sum of {a} + {b} is {add(a, b)}")
| """
Just to check
"""
def add(a, b):
"""
>>> add(2, 2)
4
>>> add(2, -2)
0
"""
return a + b
if __name__ == "__main__":
a = 5
b = 6
print(f"The sum of {a} + {b} is {add(a, b)}")
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 10: https://projecteuler.net/problem=10
Summation of primes
The sum of the primes below 10 is 2 + 3 + 5 + 7 = 17.
Find the sum of all the primes below two million.
References:
- https://en.wikipedia.org/wiki/Prime_number
"""
import math
from itertools import takewhile
from typing import Iterator
def is_prime(number: int) -> bool:
"""
Returns boolean representing primality of given number num.
>>> is_prime(2)
True
>>> is_prime(3)
True
>>> is_prime(27)
False
>>> is_prime(2999)
True
"""
if number % 2 == 0 and number > 2:
return False
return all(number % i for i in range(3, int(math.sqrt(number)) + 1, 2))
def prime_generator() -> Iterator[int]:
"""
Generate a list sequence of prime numbers
"""
num = 2
while True:
if is_prime(num):
yield num
num += 1
def solution(n: int = 2000000) -> int:
"""
Returns the sum of all the primes below n.
>>> solution(1000)
76127
>>> solution(5000)
1548136
>>> solution(10000)
5736396
>>> solution(7)
10
"""
return sum(takewhile(lambda x: x < n, prime_generator()))
if __name__ == "__main__":
print(f"{solution() = }")
| """
Project Euler Problem 10: https://projecteuler.net/problem=10
Summation of primes
The sum of the primes below 10 is 2 + 3 + 5 + 7 = 17.
Find the sum of all the primes below two million.
References:
- https://en.wikipedia.org/wiki/Prime_number
"""
import math
from itertools import takewhile
from typing import Iterator
def is_prime(number: int) -> bool:
"""
Returns boolean representing primality of given number num.
>>> is_prime(2)
True
>>> is_prime(3)
True
>>> is_prime(27)
False
>>> is_prime(2999)
True
"""
if number % 2 == 0 and number > 2:
return False
return all(number % i for i in range(3, int(math.sqrt(number)) + 1, 2))
def prime_generator() -> Iterator[int]:
"""
Generate a list sequence of prime numbers
"""
num = 2
while True:
if is_prime(num):
yield num
num += 1
def solution(n: int = 2000000) -> int:
"""
Returns the sum of all the primes below n.
>>> solution(1000)
76127
>>> solution(5000)
1548136
>>> solution(10000)
5736396
>>> solution(7)
10
"""
return sum(takewhile(lambda x: x < n, prime_generator()))
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| def lower(word: str) -> str:
"""
Will convert the entire string to lowecase letters
>>> lower("wow")
'wow'
>>> lower("HellZo")
'hellzo'
>>> lower("WHAT")
'what'
>>> lower("wh[]32")
'wh[]32'
>>> lower("whAT")
'what'
"""
# converting to ascii value int value and checking to see if char is a capital
# letter if it is a capital letter it is getting shift by 32 which makes it a lower
# case letter
return "".join(chr(ord(char) + 32) if "A" <= char <= "Z" else char for char in word)
if __name__ == "__main__":
from doctest import testmod
testmod()
| def lower(word: str) -> str:
"""
Will convert the entire string to lowecase letters
>>> lower("wow")
'wow'
>>> lower("HellZo")
'hellzo'
>>> lower("WHAT")
'what'
>>> lower("wh[]32")
'wh[]32'
>>> lower("whAT")
'what'
"""
# converting to ascii value int value and checking to see if char is a capital
# letter if it is a capital letter it is getting shift by 32 which makes it a lower
# case letter
return "".join(chr(ord(char) + 32) if "A" <= char <= "Z" else char for char in word)
if __name__ == "__main__":
from doctest import testmod
testmod()
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
python/black : true
flake8 : passed
"""
from typing import Iterator, Optional
class RedBlackTree:
"""
A Red-Black tree, which is a self-balancing BST (binary search
tree).
This tree has similar performance to AVL trees, but the balancing is
less strict, so it will perform faster for writing/deleting nodes
and slower for reading in the average case, though, because they're
both balanced binary search trees, both will get the same asymptotic
performance.
To read more about them, https://en.wikipedia.org/wiki/Red–black_tree
Unless otherwise specified, all asymptotic runtimes are specified in
terms of the size of the tree.
"""
def __init__(
self,
label: Optional[int] = None,
color: int = 0,
parent: Optional["RedBlackTree"] = None,
left: Optional["RedBlackTree"] = None,
right: Optional["RedBlackTree"] = None,
) -> None:
"""Initialize a new Red-Black Tree node with the given values:
label: The value associated with this node
color: 0 if black, 1 if red
parent: The parent to this node
left: This node's left child
right: This node's right child
"""
self.label = label
self.parent = parent
self.left = left
self.right = right
self.color = color
# Here are functions which are specific to red-black trees
def rotate_left(self) -> "RedBlackTree":
"""Rotate the subtree rooted at this node to the left and
returns the new root to this subtree.
Performing one rotation can be done in O(1).
"""
parent = self.parent
right = self.right
self.right = right.left
if self.right:
self.right.parent = self
self.parent = right
right.left = self
if parent is not None:
if parent.left == self:
parent.left = right
else:
parent.right = right
right.parent = parent
return right
def rotate_right(self) -> "RedBlackTree":
"""Rotate the subtree rooted at this node to the right and
returns the new root to this subtree.
Performing one rotation can be done in O(1).
"""
parent = self.parent
left = self.left
self.left = left.right
if self.left:
self.left.parent = self
self.parent = left
left.right = self
if parent is not None:
if parent.right is self:
parent.right = left
else:
parent.left = left
left.parent = parent
return left
def insert(self, label: int) -> "RedBlackTree":
"""Inserts label into the subtree rooted at self, performs any
rotations necessary to maintain balance, and then returns the
new root to this subtree (likely self).
This is guaranteed to run in O(log(n)) time.
"""
if self.label is None:
# Only possible with an empty tree
self.label = label
return self
if self.label == label:
return self
elif self.label > label:
if self.left:
self.left.insert(label)
else:
self.left = RedBlackTree(label, 1, self)
self.left._insert_repair()
else:
if self.right:
self.right.insert(label)
else:
self.right = RedBlackTree(label, 1, self)
self.right._insert_repair()
return self.parent or self
def _insert_repair(self) -> None:
"""Repair the coloring from inserting into a tree."""
if self.parent is None:
# This node is the root, so it just needs to be black
self.color = 0
elif color(self.parent) == 0:
# If the parent is black, then it just needs to be red
self.color = 1
else:
uncle = self.parent.sibling
if color(uncle) == 0:
if self.is_left() and self.parent.is_right():
self.parent.rotate_right()
self.right._insert_repair()
elif self.is_right() and self.parent.is_left():
self.parent.rotate_left()
self.left._insert_repair()
elif self.is_left():
self.grandparent.rotate_right()
self.parent.color = 0
self.parent.right.color = 1
else:
self.grandparent.rotate_left()
self.parent.color = 0
self.parent.left.color = 1
else:
self.parent.color = 0
uncle.color = 0
self.grandparent.color = 1
self.grandparent._insert_repair()
def remove(self, label: int) -> "RedBlackTree":
"""Remove label from this tree."""
if self.label == label:
if self.left and self.right:
# It's easier to balance a node with at most one child,
# so we replace this node with the greatest one less than
# it and remove that.
value = self.left.get_max()
self.label = value
self.left.remove(value)
else:
# This node has at most one non-None child, so we don't
# need to replace
child = self.left or self.right
if self.color == 1:
# This node is red, and its child is black
# The only way this happens to a node with one child
# is if both children are None leaves.
# We can just remove this node and call it a day.
if self.is_left():
self.parent.left = None
else:
self.parent.right = None
else:
# The node is black
if child is None:
# This node and its child are black
if self.parent is None:
# The tree is now empty
return RedBlackTree(None)
else:
self._remove_repair()
if self.is_left():
self.parent.left = None
else:
self.parent.right = None
self.parent = None
else:
# This node is black and its child is red
# Move the child node here and make it black
self.label = child.label
self.left = child.left
self.right = child.right
if self.left:
self.left.parent = self
if self.right:
self.right.parent = self
elif self.label > label:
if self.left:
self.left.remove(label)
else:
if self.right:
self.right.remove(label)
return self.parent or self
def _remove_repair(self) -> None:
"""Repair the coloring of the tree that may have been messed up."""
if color(self.sibling) == 1:
self.sibling.color = 0
self.parent.color = 1
if self.is_left():
self.parent.rotate_left()
else:
self.parent.rotate_right()
if (
color(self.parent) == 0
and color(self.sibling) == 0
and color(self.sibling.left) == 0
and color(self.sibling.right) == 0
):
self.sibling.color = 1
self.parent._remove_repair()
return
if (
color(self.parent) == 1
and color(self.sibling) == 0
and color(self.sibling.left) == 0
and color(self.sibling.right) == 0
):
self.sibling.color = 1
self.parent.color = 0
return
if (
self.is_left()
and color(self.sibling) == 0
and color(self.sibling.right) == 0
and color(self.sibling.left) == 1
):
self.sibling.rotate_right()
self.sibling.color = 0
self.sibling.right.color = 1
if (
self.is_right()
and color(self.sibling) == 0
and color(self.sibling.right) == 1
and color(self.sibling.left) == 0
):
self.sibling.rotate_left()
self.sibling.color = 0
self.sibling.left.color = 1
if (
self.is_left()
and color(self.sibling) == 0
and color(self.sibling.right) == 1
):
self.parent.rotate_left()
self.grandparent.color = self.parent.color
self.parent.color = 0
self.parent.sibling.color = 0
if (
self.is_right()
and color(self.sibling) == 0
and color(self.sibling.left) == 1
):
self.parent.rotate_right()
self.grandparent.color = self.parent.color
self.parent.color = 0
self.parent.sibling.color = 0
def check_color_properties(self) -> bool:
"""Check the coloring of the tree, and return True iff the tree
is colored in a way which matches these five properties:
(wording stolen from wikipedia article)
1. Each node is either red or black.
2. The root node is black.
3. All leaves are black.
4. If a node is red, then both its children are black.
5. Every path from any node to all of its descendent NIL nodes
has the same number of black nodes.
This function runs in O(n) time, because properties 4 and 5 take
that long to check.
"""
# I assume property 1 to hold because there is nothing that can
# make the color be anything other than 0 or 1.
# Property 2
if self.color:
# The root was red
print("Property 2")
return False
# Property 3 does not need to be checked, because None is assumed
# to be black and is all the leaves.
# Property 4
if not self.check_coloring():
print("Property 4")
return False
# Property 5
if self.black_height() is None:
print("Property 5")
return False
# All properties were met
return True
def check_coloring(self) -> None:
"""A helper function to recursively check Property 4 of a
Red-Black Tree. See check_color_properties for more info.
"""
if self.color == 1:
if color(self.left) == 1 or color(self.right) == 1:
return False
if self.left and not self.left.check_coloring():
return False
if self.right and not self.right.check_coloring():
return False
return True
def black_height(self) -> int:
"""Returns the number of black nodes from this node to the
leaves of the tree, or None if there isn't one such value (the
tree is color incorrectly).
"""
if self is None:
# If we're already at a leaf, there is no path
return 1
left = RedBlackTree.black_height(self.left)
right = RedBlackTree.black_height(self.right)
if left is None or right is None:
# There are issues with coloring below children nodes
return None
if left != right:
# The two children have unequal depths
return None
# Return the black depth of children, plus one if this node is
# black
return left + (1 - self.color)
# Here are functions which are general to all binary search trees
def __contains__(self, label) -> bool:
"""Search through the tree for label, returning True iff it is
found somewhere in the tree.
Guaranteed to run in O(log(n)) time.
"""
return self.search(label) is not None
def search(self, label: int) -> "RedBlackTree":
"""Search through the tree for label, returning its node if
it's found, and None otherwise.
This method is guaranteed to run in O(log(n)) time.
"""
if self.label == label:
return self
elif label > self.label:
if self.right is None:
return None
else:
return self.right.search(label)
else:
if self.left is None:
return None
else:
return self.left.search(label)
def floor(self, label: int) -> int:
"""Returns the largest element in this tree which is at most label.
This method is guaranteed to run in O(log(n)) time."""
if self.label == label:
return self.label
elif self.label > label:
if self.left:
return self.left.floor(label)
else:
return None
else:
if self.right:
attempt = self.right.floor(label)
if attempt is not None:
return attempt
return self.label
def ceil(self, label: int) -> int:
"""Returns the smallest element in this tree which is at least label.
This method is guaranteed to run in O(log(n)) time.
"""
if self.label == label:
return self.label
elif self.label < label:
if self.right:
return self.right.ceil(label)
else:
return None
else:
if self.left:
attempt = self.left.ceil(label)
if attempt is not None:
return attempt
return self.label
def get_max(self) -> int:
"""Returns the largest element in this tree.
This method is guaranteed to run in O(log(n)) time.
"""
if self.right:
# Go as far right as possible
return self.right.get_max()
else:
return self.label
def get_min(self) -> int:
"""Returns the smallest element in this tree.
This method is guaranteed to run in O(log(n)) time.
"""
if self.left:
# Go as far left as possible
return self.left.get_min()
else:
return self.label
@property
def grandparent(self) -> "RedBlackTree":
"""Get the current node's grandparent, or None if it doesn't exist."""
if self.parent is None:
return None
else:
return self.parent.parent
@property
def sibling(self) -> "RedBlackTree":
"""Get the current node's sibling, or None if it doesn't exist."""
if self.parent is None:
return None
elif self.parent.left is self:
return self.parent.right
else:
return self.parent.left
def is_left(self) -> bool:
"""Returns true iff this node is the left child of its parent."""
return self.parent and self.parent.left is self
def is_right(self) -> bool:
"""Returns true iff this node is the right child of its parent."""
return self.parent and self.parent.right is self
def __bool__(self) -> bool:
return True
def __len__(self) -> int:
"""
Return the number of nodes in this tree.
"""
ln = 1
if self.left:
ln += len(self.left)
if self.right:
ln += len(self.right)
return ln
def preorder_traverse(self) -> Iterator[int]:
yield self.label
if self.left:
yield from self.left.preorder_traverse()
if self.right:
yield from self.right.preorder_traverse()
def inorder_traverse(self) -> Iterator[int]:
if self.left:
yield from self.left.inorder_traverse()
yield self.label
if self.right:
yield from self.right.inorder_traverse()
def postorder_traverse(self) -> Iterator[int]:
if self.left:
yield from self.left.postorder_traverse()
if self.right:
yield from self.right.postorder_traverse()
yield self.label
def __repr__(self) -> str:
from pprint import pformat
if self.left is None and self.right is None:
return f"'{self.label} {(self.color and 'red') or 'blk'}'"
return pformat(
{
f"{self.label} {(self.color and 'red') or 'blk'}": (
self.left,
self.right,
)
},
indent=1,
)
def __eq__(self, other) -> bool:
"""Test if two trees are equal."""
if self.label == other.label:
return self.left == other.left and self.right == other.right
else:
return False
def color(node) -> int:
"""Returns the color of a node, allowing for None leaves."""
if node is None:
return 0
else:
return node.color
"""
Code for testing the various
functions of the red-black tree.
"""
def test_rotations() -> bool:
"""Test that the rotate_left and rotate_right functions work."""
# Make a tree to test on
tree = RedBlackTree(0)
tree.left = RedBlackTree(-10, parent=tree)
tree.right = RedBlackTree(10, parent=tree)
tree.left.left = RedBlackTree(-20, parent=tree.left)
tree.left.right = RedBlackTree(-5, parent=tree.left)
tree.right.left = RedBlackTree(5, parent=tree.right)
tree.right.right = RedBlackTree(20, parent=tree.right)
# Make the right rotation
left_rot = RedBlackTree(10)
left_rot.left = RedBlackTree(0, parent=left_rot)
left_rot.left.left = RedBlackTree(-10, parent=left_rot.left)
left_rot.left.right = RedBlackTree(5, parent=left_rot.left)
left_rot.left.left.left = RedBlackTree(-20, parent=left_rot.left.left)
left_rot.left.left.right = RedBlackTree(-5, parent=left_rot.left.left)
left_rot.right = RedBlackTree(20, parent=left_rot)
tree = tree.rotate_left()
if tree != left_rot:
return False
tree = tree.rotate_right()
tree = tree.rotate_right()
# Make the left rotation
right_rot = RedBlackTree(-10)
right_rot.left = RedBlackTree(-20, parent=right_rot)
right_rot.right = RedBlackTree(0, parent=right_rot)
right_rot.right.left = RedBlackTree(-5, parent=right_rot.right)
right_rot.right.right = RedBlackTree(10, parent=right_rot.right)
right_rot.right.right.left = RedBlackTree(5, parent=right_rot.right.right)
right_rot.right.right.right = RedBlackTree(20, parent=right_rot.right.right)
if tree != right_rot:
return False
return True
def test_insertion_speed() -> bool:
"""Test that the tree balances inserts to O(log(n)) by doing a lot
of them.
"""
tree = RedBlackTree(-1)
for i in range(300000):
tree = tree.insert(i)
return True
def test_insert() -> bool:
"""Test the insert() method of the tree correctly balances, colors,
and inserts.
"""
tree = RedBlackTree(0)
tree.insert(8)
tree.insert(-8)
tree.insert(4)
tree.insert(12)
tree.insert(10)
tree.insert(11)
ans = RedBlackTree(0, 0)
ans.left = RedBlackTree(-8, 0, ans)
ans.right = RedBlackTree(8, 1, ans)
ans.right.left = RedBlackTree(4, 0, ans.right)
ans.right.right = RedBlackTree(11, 0, ans.right)
ans.right.right.left = RedBlackTree(10, 1, ans.right.right)
ans.right.right.right = RedBlackTree(12, 1, ans.right.right)
return tree == ans
def test_insert_and_search() -> bool:
"""Tests searching through the tree for values."""
tree = RedBlackTree(0)
tree.insert(8)
tree.insert(-8)
tree.insert(4)
tree.insert(12)
tree.insert(10)
tree.insert(11)
if 5 in tree or -6 in tree or -10 in tree or 13 in tree:
# Found something not in there
return False
if not (11 in tree and 12 in tree and -8 in tree and 0 in tree):
# Didn't find something in there
return False
return True
def test_insert_delete() -> bool:
"""Test the insert() and delete() method of the tree, verifying the
insertion and removal of elements, and the balancing of the tree.
"""
tree = RedBlackTree(0)
tree = tree.insert(-12)
tree = tree.insert(8)
tree = tree.insert(-8)
tree = tree.insert(15)
tree = tree.insert(4)
tree = tree.insert(12)
tree = tree.insert(10)
tree = tree.insert(9)
tree = tree.insert(11)
tree = tree.remove(15)
tree = tree.remove(-12)
tree = tree.remove(9)
if not tree.check_color_properties():
return False
if list(tree.inorder_traverse()) != [-8, 0, 4, 8, 10, 11, 12]:
return False
return True
def test_floor_ceil() -> bool:
"""Tests the floor and ceiling functions in the tree."""
tree = RedBlackTree(0)
tree.insert(-16)
tree.insert(16)
tree.insert(8)
tree.insert(24)
tree.insert(20)
tree.insert(22)
tuples = [(-20, None, -16), (-10, -16, 0), (8, 8, 8), (50, 24, None)]
for val, floor, ceil in tuples:
if tree.floor(val) != floor or tree.ceil(val) != ceil:
return False
return True
def test_min_max() -> bool:
"""Tests the min and max functions in the tree."""
tree = RedBlackTree(0)
tree.insert(-16)
tree.insert(16)
tree.insert(8)
tree.insert(24)
tree.insert(20)
tree.insert(22)
if tree.get_max() != 22 or tree.get_min() != -16:
return False
return True
def test_tree_traversal() -> bool:
"""Tests the three different tree traversal functions."""
tree = RedBlackTree(0)
tree = tree.insert(-16)
tree.insert(16)
tree.insert(8)
tree.insert(24)
tree.insert(20)
tree.insert(22)
if list(tree.inorder_traverse()) != [-16, 0, 8, 16, 20, 22, 24]:
return False
if list(tree.preorder_traverse()) != [0, -16, 16, 8, 22, 20, 24]:
return False
if list(tree.postorder_traverse()) != [-16, 8, 20, 24, 22, 16, 0]:
return False
return True
def test_tree_chaining() -> bool:
"""Tests the three different tree chaining functions."""
tree = RedBlackTree(0)
tree = tree.insert(-16).insert(16).insert(8).insert(24).insert(20).insert(22)
if list(tree.inorder_traverse()) != [-16, 0, 8, 16, 20, 22, 24]:
return False
if list(tree.preorder_traverse()) != [0, -16, 16, 8, 22, 20, 24]:
return False
if list(tree.postorder_traverse()) != [-16, 8, 20, 24, 22, 16, 0]:
return False
return True
def print_results(msg: str, passes: bool) -> None:
print(str(msg), "works!" if passes else "doesn't work :(")
def pytests() -> None:
assert test_rotations()
assert test_insert()
assert test_insert_and_search()
assert test_insert_delete()
assert test_floor_ceil()
assert test_tree_traversal()
assert test_tree_chaining()
def main() -> None:
"""
>>> pytests()
"""
print_results("Rotating right and left", test_rotations())
print_results("Inserting", test_insert())
print_results("Searching", test_insert_and_search())
print_results("Deleting", test_insert_delete())
print_results("Floor and ceil", test_floor_ceil())
print_results("Tree traversal", test_tree_traversal())
print_results("Tree traversal", test_tree_chaining())
print("Testing tree balancing...")
print("This should only be a few seconds.")
test_insertion_speed()
print("Done!")
if __name__ == "__main__":
main()
| """
python/black : true
flake8 : passed
"""
from typing import Iterator, Optional
class RedBlackTree:
"""
A Red-Black tree, which is a self-balancing BST (binary search
tree).
This tree has similar performance to AVL trees, but the balancing is
less strict, so it will perform faster for writing/deleting nodes
and slower for reading in the average case, though, because they're
both balanced binary search trees, both will get the same asymptotic
performance.
To read more about them, https://en.wikipedia.org/wiki/Red–black_tree
Unless otherwise specified, all asymptotic runtimes are specified in
terms of the size of the tree.
"""
def __init__(
self,
label: Optional[int] = None,
color: int = 0,
parent: Optional["RedBlackTree"] = None,
left: Optional["RedBlackTree"] = None,
right: Optional["RedBlackTree"] = None,
) -> None:
"""Initialize a new Red-Black Tree node with the given values:
label: The value associated with this node
color: 0 if black, 1 if red
parent: The parent to this node
left: This node's left child
right: This node's right child
"""
self.label = label
self.parent = parent
self.left = left
self.right = right
self.color = color
# Here are functions which are specific to red-black trees
def rotate_left(self) -> "RedBlackTree":
"""Rotate the subtree rooted at this node to the left and
returns the new root to this subtree.
Performing one rotation can be done in O(1).
"""
parent = self.parent
right = self.right
self.right = right.left
if self.right:
self.right.parent = self
self.parent = right
right.left = self
if parent is not None:
if parent.left == self:
parent.left = right
else:
parent.right = right
right.parent = parent
return right
def rotate_right(self) -> "RedBlackTree":
"""Rotate the subtree rooted at this node to the right and
returns the new root to this subtree.
Performing one rotation can be done in O(1).
"""
parent = self.parent
left = self.left
self.left = left.right
if self.left:
self.left.parent = self
self.parent = left
left.right = self
if parent is not None:
if parent.right is self:
parent.right = left
else:
parent.left = left
left.parent = parent
return left
def insert(self, label: int) -> "RedBlackTree":
"""Inserts label into the subtree rooted at self, performs any
rotations necessary to maintain balance, and then returns the
new root to this subtree (likely self).
This is guaranteed to run in O(log(n)) time.
"""
if self.label is None:
# Only possible with an empty tree
self.label = label
return self
if self.label == label:
return self
elif self.label > label:
if self.left:
self.left.insert(label)
else:
self.left = RedBlackTree(label, 1, self)
self.left._insert_repair()
else:
if self.right:
self.right.insert(label)
else:
self.right = RedBlackTree(label, 1, self)
self.right._insert_repair()
return self.parent or self
def _insert_repair(self) -> None:
"""Repair the coloring from inserting into a tree."""
if self.parent is None:
# This node is the root, so it just needs to be black
self.color = 0
elif color(self.parent) == 0:
# If the parent is black, then it just needs to be red
self.color = 1
else:
uncle = self.parent.sibling
if color(uncle) == 0:
if self.is_left() and self.parent.is_right():
self.parent.rotate_right()
self.right._insert_repair()
elif self.is_right() and self.parent.is_left():
self.parent.rotate_left()
self.left._insert_repair()
elif self.is_left():
self.grandparent.rotate_right()
self.parent.color = 0
self.parent.right.color = 1
else:
self.grandparent.rotate_left()
self.parent.color = 0
self.parent.left.color = 1
else:
self.parent.color = 0
uncle.color = 0
self.grandparent.color = 1
self.grandparent._insert_repair()
def remove(self, label: int) -> "RedBlackTree":
"""Remove label from this tree."""
if self.label == label:
if self.left and self.right:
# It's easier to balance a node with at most one child,
# so we replace this node with the greatest one less than
# it and remove that.
value = self.left.get_max()
self.label = value
self.left.remove(value)
else:
# This node has at most one non-None child, so we don't
# need to replace
child = self.left or self.right
if self.color == 1:
# This node is red, and its child is black
# The only way this happens to a node with one child
# is if both children are None leaves.
# We can just remove this node and call it a day.
if self.is_left():
self.parent.left = None
else:
self.parent.right = None
else:
# The node is black
if child is None:
# This node and its child are black
if self.parent is None:
# The tree is now empty
return RedBlackTree(None)
else:
self._remove_repair()
if self.is_left():
self.parent.left = None
else:
self.parent.right = None
self.parent = None
else:
# This node is black and its child is red
# Move the child node here and make it black
self.label = child.label
self.left = child.left
self.right = child.right
if self.left:
self.left.parent = self
if self.right:
self.right.parent = self
elif self.label > label:
if self.left:
self.left.remove(label)
else:
if self.right:
self.right.remove(label)
return self.parent or self
def _remove_repair(self) -> None:
"""Repair the coloring of the tree that may have been messed up."""
if color(self.sibling) == 1:
self.sibling.color = 0
self.parent.color = 1
if self.is_left():
self.parent.rotate_left()
else:
self.parent.rotate_right()
if (
color(self.parent) == 0
and color(self.sibling) == 0
and color(self.sibling.left) == 0
and color(self.sibling.right) == 0
):
self.sibling.color = 1
self.parent._remove_repair()
return
if (
color(self.parent) == 1
and color(self.sibling) == 0
and color(self.sibling.left) == 0
and color(self.sibling.right) == 0
):
self.sibling.color = 1
self.parent.color = 0
return
if (
self.is_left()
and color(self.sibling) == 0
and color(self.sibling.right) == 0
and color(self.sibling.left) == 1
):
self.sibling.rotate_right()
self.sibling.color = 0
self.sibling.right.color = 1
if (
self.is_right()
and color(self.sibling) == 0
and color(self.sibling.right) == 1
and color(self.sibling.left) == 0
):
self.sibling.rotate_left()
self.sibling.color = 0
self.sibling.left.color = 1
if (
self.is_left()
and color(self.sibling) == 0
and color(self.sibling.right) == 1
):
self.parent.rotate_left()
self.grandparent.color = self.parent.color
self.parent.color = 0
self.parent.sibling.color = 0
if (
self.is_right()
and color(self.sibling) == 0
and color(self.sibling.left) == 1
):
self.parent.rotate_right()
self.grandparent.color = self.parent.color
self.parent.color = 0
self.parent.sibling.color = 0
def check_color_properties(self) -> bool:
"""Check the coloring of the tree, and return True iff the tree
is colored in a way which matches these five properties:
(wording stolen from wikipedia article)
1. Each node is either red or black.
2. The root node is black.
3. All leaves are black.
4. If a node is red, then both its children are black.
5. Every path from any node to all of its descendent NIL nodes
has the same number of black nodes.
This function runs in O(n) time, because properties 4 and 5 take
that long to check.
"""
# I assume property 1 to hold because there is nothing that can
# make the color be anything other than 0 or 1.
# Property 2
if self.color:
# The root was red
print("Property 2")
return False
# Property 3 does not need to be checked, because None is assumed
# to be black and is all the leaves.
# Property 4
if not self.check_coloring():
print("Property 4")
return False
# Property 5
if self.black_height() is None:
print("Property 5")
return False
# All properties were met
return True
def check_coloring(self) -> None:
"""A helper function to recursively check Property 4 of a
Red-Black Tree. See check_color_properties for more info.
"""
if self.color == 1:
if color(self.left) == 1 or color(self.right) == 1:
return False
if self.left and not self.left.check_coloring():
return False
if self.right and not self.right.check_coloring():
return False
return True
def black_height(self) -> int:
"""Returns the number of black nodes from this node to the
leaves of the tree, or None if there isn't one such value (the
tree is color incorrectly).
"""
if self is None:
# If we're already at a leaf, there is no path
return 1
left = RedBlackTree.black_height(self.left)
right = RedBlackTree.black_height(self.right)
if left is None or right is None:
# There are issues with coloring below children nodes
return None
if left != right:
# The two children have unequal depths
return None
# Return the black depth of children, plus one if this node is
# black
return left + (1 - self.color)
# Here are functions which are general to all binary search trees
def __contains__(self, label) -> bool:
"""Search through the tree for label, returning True iff it is
found somewhere in the tree.
Guaranteed to run in O(log(n)) time.
"""
return self.search(label) is not None
def search(self, label: int) -> "RedBlackTree":
"""Search through the tree for label, returning its node if
it's found, and None otherwise.
This method is guaranteed to run in O(log(n)) time.
"""
if self.label == label:
return self
elif label > self.label:
if self.right is None:
return None
else:
return self.right.search(label)
else:
if self.left is None:
return None
else:
return self.left.search(label)
def floor(self, label: int) -> int:
"""Returns the largest element in this tree which is at most label.
This method is guaranteed to run in O(log(n)) time."""
if self.label == label:
return self.label
elif self.label > label:
if self.left:
return self.left.floor(label)
else:
return None
else:
if self.right:
attempt = self.right.floor(label)
if attempt is not None:
return attempt
return self.label
def ceil(self, label: int) -> int:
"""Returns the smallest element in this tree which is at least label.
This method is guaranteed to run in O(log(n)) time.
"""
if self.label == label:
return self.label
elif self.label < label:
if self.right:
return self.right.ceil(label)
else:
return None
else:
if self.left:
attempt = self.left.ceil(label)
if attempt is not None:
return attempt
return self.label
def get_max(self) -> int:
"""Returns the largest element in this tree.
This method is guaranteed to run in O(log(n)) time.
"""
if self.right:
# Go as far right as possible
return self.right.get_max()
else:
return self.label
def get_min(self) -> int:
"""Returns the smallest element in this tree.
This method is guaranteed to run in O(log(n)) time.
"""
if self.left:
# Go as far left as possible
return self.left.get_min()
else:
return self.label
@property
def grandparent(self) -> "RedBlackTree":
"""Get the current node's grandparent, or None if it doesn't exist."""
if self.parent is None:
return None
else:
return self.parent.parent
@property
def sibling(self) -> "RedBlackTree":
"""Get the current node's sibling, or None if it doesn't exist."""
if self.parent is None:
return None
elif self.parent.left is self:
return self.parent.right
else:
return self.parent.left
def is_left(self) -> bool:
"""Returns true iff this node is the left child of its parent."""
return self.parent and self.parent.left is self
def is_right(self) -> bool:
"""Returns true iff this node is the right child of its parent."""
return self.parent and self.parent.right is self
def __bool__(self) -> bool:
return True
def __len__(self) -> int:
"""
Return the number of nodes in this tree.
"""
ln = 1
if self.left:
ln += len(self.left)
if self.right:
ln += len(self.right)
return ln
def preorder_traverse(self) -> Iterator[int]:
yield self.label
if self.left:
yield from self.left.preorder_traverse()
if self.right:
yield from self.right.preorder_traverse()
def inorder_traverse(self) -> Iterator[int]:
if self.left:
yield from self.left.inorder_traverse()
yield self.label
if self.right:
yield from self.right.inorder_traverse()
def postorder_traverse(self) -> Iterator[int]:
if self.left:
yield from self.left.postorder_traverse()
if self.right:
yield from self.right.postorder_traverse()
yield self.label
def __repr__(self) -> str:
from pprint import pformat
if self.left is None and self.right is None:
return f"'{self.label} {(self.color and 'red') or 'blk'}'"
return pformat(
{
f"{self.label} {(self.color and 'red') or 'blk'}": (
self.left,
self.right,
)
},
indent=1,
)
def __eq__(self, other) -> bool:
"""Test if two trees are equal."""
if self.label == other.label:
return self.left == other.left and self.right == other.right
else:
return False
def color(node) -> int:
"""Returns the color of a node, allowing for None leaves."""
if node is None:
return 0
else:
return node.color
"""
Code for testing the various
functions of the red-black tree.
"""
def test_rotations() -> bool:
"""Test that the rotate_left and rotate_right functions work."""
# Make a tree to test on
tree = RedBlackTree(0)
tree.left = RedBlackTree(-10, parent=tree)
tree.right = RedBlackTree(10, parent=tree)
tree.left.left = RedBlackTree(-20, parent=tree.left)
tree.left.right = RedBlackTree(-5, parent=tree.left)
tree.right.left = RedBlackTree(5, parent=tree.right)
tree.right.right = RedBlackTree(20, parent=tree.right)
# Make the right rotation
left_rot = RedBlackTree(10)
left_rot.left = RedBlackTree(0, parent=left_rot)
left_rot.left.left = RedBlackTree(-10, parent=left_rot.left)
left_rot.left.right = RedBlackTree(5, parent=left_rot.left)
left_rot.left.left.left = RedBlackTree(-20, parent=left_rot.left.left)
left_rot.left.left.right = RedBlackTree(-5, parent=left_rot.left.left)
left_rot.right = RedBlackTree(20, parent=left_rot)
tree = tree.rotate_left()
if tree != left_rot:
return False
tree = tree.rotate_right()
tree = tree.rotate_right()
# Make the left rotation
right_rot = RedBlackTree(-10)
right_rot.left = RedBlackTree(-20, parent=right_rot)
right_rot.right = RedBlackTree(0, parent=right_rot)
right_rot.right.left = RedBlackTree(-5, parent=right_rot.right)
right_rot.right.right = RedBlackTree(10, parent=right_rot.right)
right_rot.right.right.left = RedBlackTree(5, parent=right_rot.right.right)
right_rot.right.right.right = RedBlackTree(20, parent=right_rot.right.right)
if tree != right_rot:
return False
return True
def test_insertion_speed() -> bool:
"""Test that the tree balances inserts to O(log(n)) by doing a lot
of them.
"""
tree = RedBlackTree(-1)
for i in range(300000):
tree = tree.insert(i)
return True
def test_insert() -> bool:
"""Test the insert() method of the tree correctly balances, colors,
and inserts.
"""
tree = RedBlackTree(0)
tree.insert(8)
tree.insert(-8)
tree.insert(4)
tree.insert(12)
tree.insert(10)
tree.insert(11)
ans = RedBlackTree(0, 0)
ans.left = RedBlackTree(-8, 0, ans)
ans.right = RedBlackTree(8, 1, ans)
ans.right.left = RedBlackTree(4, 0, ans.right)
ans.right.right = RedBlackTree(11, 0, ans.right)
ans.right.right.left = RedBlackTree(10, 1, ans.right.right)
ans.right.right.right = RedBlackTree(12, 1, ans.right.right)
return tree == ans
def test_insert_and_search() -> bool:
"""Tests searching through the tree for values."""
tree = RedBlackTree(0)
tree.insert(8)
tree.insert(-8)
tree.insert(4)
tree.insert(12)
tree.insert(10)
tree.insert(11)
if 5 in tree or -6 in tree or -10 in tree or 13 in tree:
# Found something not in there
return False
if not (11 in tree and 12 in tree and -8 in tree and 0 in tree):
# Didn't find something in there
return False
return True
def test_insert_delete() -> bool:
"""Test the insert() and delete() method of the tree, verifying the
insertion and removal of elements, and the balancing of the tree.
"""
tree = RedBlackTree(0)
tree = tree.insert(-12)
tree = tree.insert(8)
tree = tree.insert(-8)
tree = tree.insert(15)
tree = tree.insert(4)
tree = tree.insert(12)
tree = tree.insert(10)
tree = tree.insert(9)
tree = tree.insert(11)
tree = tree.remove(15)
tree = tree.remove(-12)
tree = tree.remove(9)
if not tree.check_color_properties():
return False
if list(tree.inorder_traverse()) != [-8, 0, 4, 8, 10, 11, 12]:
return False
return True
def test_floor_ceil() -> bool:
"""Tests the floor and ceiling functions in the tree."""
tree = RedBlackTree(0)
tree.insert(-16)
tree.insert(16)
tree.insert(8)
tree.insert(24)
tree.insert(20)
tree.insert(22)
tuples = [(-20, None, -16), (-10, -16, 0), (8, 8, 8), (50, 24, None)]
for val, floor, ceil in tuples:
if tree.floor(val) != floor or tree.ceil(val) != ceil:
return False
return True
def test_min_max() -> bool:
"""Tests the min and max functions in the tree."""
tree = RedBlackTree(0)
tree.insert(-16)
tree.insert(16)
tree.insert(8)
tree.insert(24)
tree.insert(20)
tree.insert(22)
if tree.get_max() != 22 or tree.get_min() != -16:
return False
return True
def test_tree_traversal() -> bool:
"""Tests the three different tree traversal functions."""
tree = RedBlackTree(0)
tree = tree.insert(-16)
tree.insert(16)
tree.insert(8)
tree.insert(24)
tree.insert(20)
tree.insert(22)
if list(tree.inorder_traverse()) != [-16, 0, 8, 16, 20, 22, 24]:
return False
if list(tree.preorder_traverse()) != [0, -16, 16, 8, 22, 20, 24]:
return False
if list(tree.postorder_traverse()) != [-16, 8, 20, 24, 22, 16, 0]:
return False
return True
def test_tree_chaining() -> bool:
"""Tests the three different tree chaining functions."""
tree = RedBlackTree(0)
tree = tree.insert(-16).insert(16).insert(8).insert(24).insert(20).insert(22)
if list(tree.inorder_traverse()) != [-16, 0, 8, 16, 20, 22, 24]:
return False
if list(tree.preorder_traverse()) != [0, -16, 16, 8, 22, 20, 24]:
return False
if list(tree.postorder_traverse()) != [-16, 8, 20, 24, 22, 16, 0]:
return False
return True
def print_results(msg: str, passes: bool) -> None:
print(str(msg), "works!" if passes else "doesn't work :(")
def pytests() -> None:
assert test_rotations()
assert test_insert()
assert test_insert_and_search()
assert test_insert_delete()
assert test_floor_ceil()
assert test_tree_traversal()
assert test_tree_chaining()
def main() -> None:
"""
>>> pytests()
"""
print_results("Rotating right and left", test_rotations())
print_results("Inserting", test_insert())
print_results("Searching", test_insert_and_search())
print_results("Deleting", test_insert_delete())
print_results("Floor and ceil", test_floor_ceil())
print_results("Tree traversal", test_tree_traversal())
print_results("Tree traversal", test_tree_chaining())
print("Testing tree balancing...")
print("This should only be a few seconds.")
test_insertion_speed()
print("Done!")
if __name__ == "__main__":
main()
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # git ls-files --others --exclude-from=.git/info/exclude
# Lines that start with '#' are comments.
# For a project mostly in C, the following would be a good set of
# exclude patterns (uncomment them if you want to use them):
# *.[oa]
# *~
| # git ls-files --others --exclude-from=.git/info/exclude
# Lines that start with '#' are comments.
# For a project mostly in C, the following would be a good set of
# exclude patterns (uncomment them if you want to use them):
# *.[oa]
# *~
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 77: https://projecteuler.net/problem=77
It is possible to write ten as the sum of primes in exactly five different ways:
7 + 3
5 + 5
5 + 3 + 2
3 + 3 + 2 + 2
2 + 2 + 2 + 2 + 2
What is the first value which can be written as the sum of primes in over
five thousand different ways?
"""
from functools import lru_cache
from math import ceil
from typing import Optional, Set
NUM_PRIMES = 100
primes = set(range(3, NUM_PRIMES, 2))
primes.add(2)
prime: int
for prime in range(3, ceil(NUM_PRIMES ** 0.5), 2):
if prime not in primes:
continue
primes.difference_update(set(range(prime * prime, NUM_PRIMES, prime)))
@lru_cache(maxsize=100)
def partition(number_to_partition: int) -> Set[int]:
"""
Return a set of integers corresponding to unique prime partitions of n.
The unique prime partitions can be represented as unique prime decompositions,
e.g. (7+3) <-> 7*3 = 12, (3+3+2+2) = 3*3*2*2 = 36
>>> partition(10)
{32, 36, 21, 25, 30}
>>> partition(15)
{192, 160, 105, 44, 112, 243, 180, 150, 216, 26, 125, 126}
>>> len(partition(20))
26
"""
if number_to_partition < 0:
return set()
elif number_to_partition == 0:
return {1}
ret: Set[int] = set()
prime: int
sub: int
for prime in primes:
if prime > number_to_partition:
continue
for sub in partition(number_to_partition - prime):
ret.add(sub * prime)
return ret
def solution(number_unique_partitions: int = 5000) -> Optional[int]:
"""
Return the smallest integer that can be written as the sum of primes in over
m unique ways.
>>> solution(4)
10
>>> solution(500)
45
>>> solution(1000)
53
"""
for number_to_partition in range(1, NUM_PRIMES):
if len(partition(number_to_partition)) > number_unique_partitions:
return number_to_partition
return None
if __name__ == "__main__":
print(f"{solution() = }")
| """
Project Euler Problem 77: https://projecteuler.net/problem=77
It is possible to write ten as the sum of primes in exactly five different ways:
7 + 3
5 + 5
5 + 3 + 2
3 + 3 + 2 + 2
2 + 2 + 2 + 2 + 2
What is the first value which can be written as the sum of primes in over
five thousand different ways?
"""
from functools import lru_cache
from math import ceil
from typing import Optional, Set
NUM_PRIMES = 100
primes = set(range(3, NUM_PRIMES, 2))
primes.add(2)
prime: int
for prime in range(3, ceil(NUM_PRIMES ** 0.5), 2):
if prime not in primes:
continue
primes.difference_update(set(range(prime * prime, NUM_PRIMES, prime)))
@lru_cache(maxsize=100)
def partition(number_to_partition: int) -> Set[int]:
"""
Return a set of integers corresponding to unique prime partitions of n.
The unique prime partitions can be represented as unique prime decompositions,
e.g. (7+3) <-> 7*3 = 12, (3+3+2+2) = 3*3*2*2 = 36
>>> partition(10)
{32, 36, 21, 25, 30}
>>> partition(15)
{192, 160, 105, 44, 112, 243, 180, 150, 216, 26, 125, 126}
>>> len(partition(20))
26
"""
if number_to_partition < 0:
return set()
elif number_to_partition == 0:
return {1}
ret: Set[int] = set()
prime: int
sub: int
for prime in primes:
if prime > number_to_partition:
continue
for sub in partition(number_to_partition - prime):
ret.add(sub * prime)
return ret
def solution(number_unique_partitions: int = 5000) -> Optional[int]:
"""
Return the smallest integer that can be written as the sum of primes in over
m unique ways.
>>> solution(4)
10
>>> solution(500)
45
>>> solution(1000)
53
"""
for number_to_partition in range(1, NUM_PRIMES):
if len(partition(number_to_partition)) > number_unique_partitions:
return number_to_partition
return None
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Problem 125: https://projecteuler.net/problem=125
The palindromic number 595 is interesting because it can be written as the sum
of consecutive squares: 6^2 + 7^2 + 8^2 + 9^2 + 10^2 + 11^2 + 12^2.
There are exactly eleven palindromes below one-thousand that can be written as
consecutive square sums, and the sum of these palindromes is 4164. Note that
1 = 0^2 + 1^2 has not been included as this problem is concerned with the
squares of positive integers.
Find the sum of all the numbers less than 10^8 that are both palindromic and can
be written as the sum of consecutive squares.
"""
def is_palindrome(n: int) -> bool:
"""
Check if an integer is palindromic.
>>> is_palindrome(12521)
True
>>> is_palindrome(12522)
False
>>> is_palindrome(12210)
False
"""
if n % 10 == 0:
return False
s = str(n)
return s == s[::-1]
def solution() -> int:
"""
Returns the sum of all numbers less than 1e8 that are both palindromic and
can be written as the sum of consecutive squares.
"""
LIMIT = 10 ** 8
answer = set()
first_square = 1
sum_squares = 5
while sum_squares < LIMIT:
last_square = first_square + 1
while sum_squares < LIMIT:
if is_palindrome(sum_squares):
answer.add(sum_squares)
last_square += 1
sum_squares += last_square ** 2
first_square += 1
sum_squares = first_square ** 2 + (first_square + 1) ** 2
return sum(answer)
if __name__ == "__main__":
print(solution())
| """
Problem 125: https://projecteuler.net/problem=125
The palindromic number 595 is interesting because it can be written as the sum
of consecutive squares: 6^2 + 7^2 + 8^2 + 9^2 + 10^2 + 11^2 + 12^2.
There are exactly eleven palindromes below one-thousand that can be written as
consecutive square sums, and the sum of these palindromes is 4164. Note that
1 = 0^2 + 1^2 has not been included as this problem is concerned with the
squares of positive integers.
Find the sum of all the numbers less than 10^8 that are both palindromic and can
be written as the sum of consecutive squares.
"""
def is_palindrome(n: int) -> bool:
"""
Check if an integer is palindromic.
>>> is_palindrome(12521)
True
>>> is_palindrome(12522)
False
>>> is_palindrome(12210)
False
"""
if n % 10 == 0:
return False
s = str(n)
return s == s[::-1]
def solution() -> int:
"""
Returns the sum of all numbers less than 1e8 that are both palindromic and
can be written as the sum of consecutive squares.
"""
LIMIT = 10 ** 8
answer = set()
first_square = 1
sum_squares = 5
while sum_squares < LIMIT:
last_square = first_square + 1
while sum_squares < LIMIT:
if is_palindrome(sum_squares):
answer.add(sum_squares)
last_square += 1
sum_squares += last_square ** 2
first_square += 1
sum_squares = first_square ** 2 + (first_square + 1) ** 2
return sum(answer)
if __name__ == "__main__":
print(solution())
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Problem 81: https://projecteuler.net/problem=81
In the 5 by 5 matrix below, the minimal path sum from the top left to the bottom right,
by only moving to the right and down, is indicated in bold red and is equal to 2427.
[131] 673 234 103 18
[201] [96] [342] 965 150
630 803 [746] [422] 111
537 699 497 [121] 956
805 732 524 [37] [331]
Find the minimal path sum from the top left to the bottom right by only moving right
and down in matrix.txt (https://projecteuler.net/project/resources/p081_matrix.txt),
a 31K text file containing an 80 by 80 matrix.
"""
import os
def solution(filename: str = "matrix.txt") -> int:
"""
Returns the minimal path sum from the top left to the bottom right of the matrix.
>>> solution()
427337
"""
with open(os.path.join(os.path.dirname(__file__), filename), "r") as in_file:
data = in_file.read()
grid = [[int(cell) for cell in row.split(",")] for row in data.strip().splitlines()]
dp = [[0 for cell in row] for row in grid]
n = len(grid[0])
dp = [[0 for i in range(n)] for j in range(n)]
dp[0][0] = grid[0][0]
for i in range(1, n):
dp[0][i] = grid[0][i] + dp[0][i - 1]
for i in range(1, n):
dp[i][0] = grid[i][0] + dp[i - 1][0]
for i in range(1, n):
for j in range(1, n):
dp[i][j] = grid[i][j] + min(dp[i - 1][j], dp[i][j - 1])
return dp[-1][-1]
if __name__ == "__main__":
print(f"{solution() = }")
| """
Problem 81: https://projecteuler.net/problem=81
In the 5 by 5 matrix below, the minimal path sum from the top left to the bottom right,
by only moving to the right and down, is indicated in bold red and is equal to 2427.
[131] 673 234 103 18
[201] [96] [342] 965 150
630 803 [746] [422] 111
537 699 497 [121] 956
805 732 524 [37] [331]
Find the minimal path sum from the top left to the bottom right by only moving right
and down in matrix.txt (https://projecteuler.net/project/resources/p081_matrix.txt),
a 31K text file containing an 80 by 80 matrix.
"""
import os
def solution(filename: str = "matrix.txt") -> int:
"""
Returns the minimal path sum from the top left to the bottom right of the matrix.
>>> solution()
427337
"""
with open(os.path.join(os.path.dirname(__file__), filename), "r") as in_file:
data = in_file.read()
grid = [[int(cell) for cell in row.split(",")] for row in data.strip().splitlines()]
dp = [[0 for cell in row] for row in grid]
n = len(grid[0])
dp = [[0 for i in range(n)] for j in range(n)]
dp[0][0] = grid[0][0]
for i in range(1, n):
dp[0][i] = grid[0][i] + dp[0][i - 1]
for i in range(1, n):
dp[i][0] = grid[i][0] + dp[i - 1][0]
for i in range(1, n):
for j in range(1, n):
dp[i][j] = grid[i][j] + min(dp[i - 1][j], dp[i][j - 1])
return dp[-1][-1]
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
You have m types of coins available in infinite quantities
where the value of each coins is given in the array S=[S0,... Sm-1]
Can you determine number of ways of making change for n units using
the given types of coins?
https://www.hackerrank.com/challenges/coin-change/problem
"""
def dp_count(S, n):
"""
>>> dp_count([1, 2, 3], 4)
4
>>> dp_count([1, 2, 3], 7)
8
>>> dp_count([2, 5, 3, 6], 10)
5
>>> dp_count([10], 99)
0
>>> dp_count([4, 5, 6], 0)
1
>>> dp_count([1, 2, 3], -5)
0
"""
if n < 0:
return 0
# table[i] represents the number of ways to get to amount i
table = [0] * (n + 1)
# There is exactly 1 way to get to zero(You pick no coins).
table[0] = 1
# Pick all coins one by one and update table[] values
# after the index greater than or equal to the value of the
# picked coin
for coin_val in S:
for j in range(coin_val, n + 1):
table[j] += table[j - coin_val]
return table[n]
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
You have m types of coins available in infinite quantities
where the value of each coins is given in the array S=[S0,... Sm-1]
Can you determine number of ways of making change for n units using
the given types of coins?
https://www.hackerrank.com/challenges/coin-change/problem
"""
def dp_count(S, n):
"""
>>> dp_count([1, 2, 3], 4)
4
>>> dp_count([1, 2, 3], 7)
8
>>> dp_count([2, 5, 3, 6], 10)
5
>>> dp_count([10], 99)
0
>>> dp_count([4, 5, 6], 0)
1
>>> dp_count([1, 2, 3], -5)
0
"""
if n < 0:
return 0
# table[i] represents the number of ways to get to amount i
table = [0] * (n + 1)
# There is exactly 1 way to get to zero(You pick no coins).
table[0] = 1
# Pick all coins one by one and update table[] values
# after the index greater than or equal to the value of the
# picked coin
for coin_val in S:
for j in range(coin_val, n + 1):
table[j] += table[j - coin_val]
return table[n]
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| def reverse_letters(input_str: str) -> str:
"""
Reverses letters in a given string without adjusting the position of the words
>>> reverse_letters('The cat in the hat')
'ehT tac ni eht tah'
>>> reverse_letters('The quick brown fox jumped over the lazy dog.')
'ehT kciuq nworb xof depmuj revo eht yzal .god'
>>> reverse_letters('Is this true?')
'sI siht ?eurt'
>>> reverse_letters("I love Python")
'I evol nohtyP'
"""
return " ".join([word[::-1] for word in input_str.split()])
if __name__ == "__main__":
import doctest
doctest.testmod()
| def reverse_letters(input_str: str) -> str:
"""
Reverses letters in a given string without adjusting the position of the words
>>> reverse_letters('The cat in the hat')
'ehT tac ni eht tah'
>>> reverse_letters('The quick brown fox jumped over the lazy dog.')
'ehT kciuq nworb xof depmuj revo eht yzal .god'
>>> reverse_letters('Is this true?')
'sI siht ?eurt'
>>> reverse_letters("I love Python")
'I evol nohtyP'
"""
return " ".join([word[::-1] for word in input_str.split()])
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| #!/usr/bin/env python
#
# Sort large text files in a minimum amount of memory
#
import argparse
import os
class FileSplitter:
BLOCK_FILENAME_FORMAT = "block_{0}.dat"
def __init__(self, filename):
self.filename = filename
self.block_filenames = []
def write_block(self, data, block_number):
filename = self.BLOCK_FILENAME_FORMAT.format(block_number)
with open(filename, "w") as file:
file.write(data)
self.block_filenames.append(filename)
def get_block_filenames(self):
return self.block_filenames
def split(self, block_size, sort_key=None):
i = 0
with open(self.filename) as file:
while True:
lines = file.readlines(block_size)
if lines == []:
break
if sort_key is None:
lines.sort()
else:
lines.sort(key=sort_key)
self.write_block("".join(lines), i)
i += 1
def cleanup(self):
map(lambda f: os.remove(f), self.block_filenames)
class NWayMerge:
def select(self, choices):
min_index = -1
min_str = None
for i in range(len(choices)):
if min_str is None or choices[i] < min_str:
min_index = i
return min_index
class FilesArray:
def __init__(self, files):
self.files = files
self.empty = set()
self.num_buffers = len(files)
self.buffers = {i: None for i in range(self.num_buffers)}
def get_dict(self):
return {
i: self.buffers[i] for i in range(self.num_buffers) if i not in self.empty
}
def refresh(self):
for i in range(self.num_buffers):
if self.buffers[i] is None and i not in self.empty:
self.buffers[i] = self.files[i].readline()
if self.buffers[i] == "":
self.empty.add(i)
self.files[i].close()
if len(self.empty) == self.num_buffers:
return False
return True
def unshift(self, index):
value = self.buffers[index]
self.buffers[index] = None
return value
class FileMerger:
def __init__(self, merge_strategy):
self.merge_strategy = merge_strategy
def merge(self, filenames, outfilename, buffer_size):
buffers = FilesArray(self.get_file_handles(filenames, buffer_size))
with open(outfilename, "w", buffer_size) as outfile:
while buffers.refresh():
min_index = self.merge_strategy.select(buffers.get_dict())
outfile.write(buffers.unshift(min_index))
def get_file_handles(self, filenames, buffer_size):
files = {}
for i in range(len(filenames)):
files[i] = open(filenames[i], "r", buffer_size)
return files
class ExternalSort:
def __init__(self, block_size):
self.block_size = block_size
def sort(self, filename, sort_key=None):
num_blocks = self.get_number_blocks(filename, self.block_size)
splitter = FileSplitter(filename)
splitter.split(self.block_size, sort_key)
merger = FileMerger(NWayMerge())
buffer_size = self.block_size / (num_blocks + 1)
merger.merge(splitter.get_block_filenames(), filename + ".out", buffer_size)
splitter.cleanup()
def get_number_blocks(self, filename, block_size):
return (os.stat(filename).st_size / block_size) + 1
def parse_memory(string):
if string[-1].lower() == "k":
return int(string[:-1]) * 1024
elif string[-1].lower() == "m":
return int(string[:-1]) * 1024 * 1024
elif string[-1].lower() == "g":
return int(string[:-1]) * 1024 * 1024 * 1024
else:
return int(string)
def main():
parser = argparse.ArgumentParser()
parser.add_argument(
"-m", "--mem", help="amount of memory to use for sorting", default="100M"
)
parser.add_argument(
"filename", metavar="<filename>", nargs=1, help="name of file to sort"
)
args = parser.parse_args()
sorter = ExternalSort(parse_memory(args.mem))
sorter.sort(args.filename[0])
if __name__ == "__main__":
main()
| #!/usr/bin/env python
#
# Sort large text files in a minimum amount of memory
#
import argparse
import os
class FileSplitter:
BLOCK_FILENAME_FORMAT = "block_{0}.dat"
def __init__(self, filename):
self.filename = filename
self.block_filenames = []
def write_block(self, data, block_number):
filename = self.BLOCK_FILENAME_FORMAT.format(block_number)
with open(filename, "w") as file:
file.write(data)
self.block_filenames.append(filename)
def get_block_filenames(self):
return self.block_filenames
def split(self, block_size, sort_key=None):
i = 0
with open(self.filename) as file:
while True:
lines = file.readlines(block_size)
if lines == []:
break
if sort_key is None:
lines.sort()
else:
lines.sort(key=sort_key)
self.write_block("".join(lines), i)
i += 1
def cleanup(self):
map(lambda f: os.remove(f), self.block_filenames)
class NWayMerge:
def select(self, choices):
min_index = -1
min_str = None
for i in range(len(choices)):
if min_str is None or choices[i] < min_str:
min_index = i
return min_index
class FilesArray:
def __init__(self, files):
self.files = files
self.empty = set()
self.num_buffers = len(files)
self.buffers = {i: None for i in range(self.num_buffers)}
def get_dict(self):
return {
i: self.buffers[i] for i in range(self.num_buffers) if i not in self.empty
}
def refresh(self):
for i in range(self.num_buffers):
if self.buffers[i] is None and i not in self.empty:
self.buffers[i] = self.files[i].readline()
if self.buffers[i] == "":
self.empty.add(i)
self.files[i].close()
if len(self.empty) == self.num_buffers:
return False
return True
def unshift(self, index):
value = self.buffers[index]
self.buffers[index] = None
return value
class FileMerger:
def __init__(self, merge_strategy):
self.merge_strategy = merge_strategy
def merge(self, filenames, outfilename, buffer_size):
buffers = FilesArray(self.get_file_handles(filenames, buffer_size))
with open(outfilename, "w", buffer_size) as outfile:
while buffers.refresh():
min_index = self.merge_strategy.select(buffers.get_dict())
outfile.write(buffers.unshift(min_index))
def get_file_handles(self, filenames, buffer_size):
files = {}
for i in range(len(filenames)):
files[i] = open(filenames[i], "r", buffer_size)
return files
class ExternalSort:
def __init__(self, block_size):
self.block_size = block_size
def sort(self, filename, sort_key=None):
num_blocks = self.get_number_blocks(filename, self.block_size)
splitter = FileSplitter(filename)
splitter.split(self.block_size, sort_key)
merger = FileMerger(NWayMerge())
buffer_size = self.block_size / (num_blocks + 1)
merger.merge(splitter.get_block_filenames(), filename + ".out", buffer_size)
splitter.cleanup()
def get_number_blocks(self, filename, block_size):
return (os.stat(filename).st_size / block_size) + 1
def parse_memory(string):
if string[-1].lower() == "k":
return int(string[:-1]) * 1024
elif string[-1].lower() == "m":
return int(string[:-1]) * 1024 * 1024
elif string[-1].lower() == "g":
return int(string[:-1]) * 1024 * 1024 * 1024
else:
return int(string)
def main():
parser = argparse.ArgumentParser()
parser.add_argument(
"-m", "--mem", help="amount of memory to use for sorting", default="100M"
)
parser.add_argument(
"filename", metavar="<filename>", nargs=1, help="name of file to sort"
)
args = parser.parse_args()
sorter = ExternalSort(parse_memory(args.mem))
sorter.sort(args.filename[0])
if __name__ == "__main__":
main()
| -1 |
TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
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TheAlgorithms/Python | 4,273 | Update our pre-commit dependencies | ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| cclauss | 2021-03-19T09:34:15Z | 2021-03-20T05:12:17Z | b8a19ccfea0ceca9f83912aa2f5ad2c15114416a | 987567360e53da1bef786364580e9d5c6dce3fc6 | Update our pre-commit dependencies. ### **Describe your change:**
* [ ] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
* [ ] Update our dependencies
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [x] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| def binary_search(lst, item, start, end):
if start == end:
return start if lst[start] > item else start + 1
if start > end:
return start
mid = (start + end) // 2
if lst[mid] < item:
return binary_search(lst, item, mid + 1, end)
elif lst[mid] > item:
return binary_search(lst, item, start, mid - 1)
else:
return mid
def insertion_sort(lst):
length = len(lst)
for index in range(1, length):
value = lst[index]
pos = binary_search(lst, value, 0, index - 1)
lst = lst[:pos] + [value] + lst[pos:index] + lst[index + 1 :]
return lst
def merge(left, right):
if not left:
return right
if not right:
return left
if left[0] < right[0]:
return [left[0]] + merge(left[1:], right)
return [right[0]] + merge(left, right[1:])
def tim_sort(lst):
"""
>>> tim_sort("Python")
['P', 'h', 'n', 'o', 't', 'y']
>>> tim_sort((1.1, 1, 0, -1, -1.1))
[-1.1, -1, 0, 1, 1.1]
>>> tim_sort(list(reversed(list(range(7)))))
[0, 1, 2, 3, 4, 5, 6]
>>> tim_sort([3, 2, 1]) == insertion_sort([3, 2, 1])
True
>>> tim_sort([3, 2, 1]) == sorted([3, 2, 1])
True
"""
length = len(lst)
runs, sorted_runs = [], []
new_run = [lst[0]]
sorted_array = []
i = 1
while i < length:
if lst[i] < lst[i - 1]:
runs.append(new_run)
new_run = [lst[i]]
else:
new_run.append(lst[i])
i += 1
runs.append(new_run)
for run in runs:
sorted_runs.append(insertion_sort(run))
for run in sorted_runs:
sorted_array = merge(sorted_array, run)
return sorted_array
def main():
lst = [5, 9, 10, 3, -4, 5, 178, 92, 46, -18, 0, 7]
sorted_lst = tim_sort(lst)
print(sorted_lst)
if __name__ == "__main__":
main()
| def binary_search(lst, item, start, end):
if start == end:
return start if lst[start] > item else start + 1
if start > end:
return start
mid = (start + end) // 2
if lst[mid] < item:
return binary_search(lst, item, mid + 1, end)
elif lst[mid] > item:
return binary_search(lst, item, start, mid - 1)
else:
return mid
def insertion_sort(lst):
length = len(lst)
for index in range(1, length):
value = lst[index]
pos = binary_search(lst, value, 0, index - 1)
lst = lst[:pos] + [value] + lst[pos:index] + lst[index + 1 :]
return lst
def merge(left, right):
if not left:
return right
if not right:
return left
if left[0] < right[0]:
return [left[0]] + merge(left[1:], right)
return [right[0]] + merge(left, right[1:])
def tim_sort(lst):
"""
>>> tim_sort("Python")
['P', 'h', 'n', 'o', 't', 'y']
>>> tim_sort((1.1, 1, 0, -1, -1.1))
[-1.1, -1, 0, 1, 1.1]
>>> tim_sort(list(reversed(list(range(7)))))
[0, 1, 2, 3, 4, 5, 6]
>>> tim_sort([3, 2, 1]) == insertion_sort([3, 2, 1])
True
>>> tim_sort([3, 2, 1]) == sorted([3, 2, 1])
True
"""
length = len(lst)
runs, sorted_runs = [], []
new_run = [lst[0]]
sorted_array = []
i = 1
while i < length:
if lst[i] < lst[i - 1]:
runs.append(new_run)
new_run = [lst[i]]
else:
new_run.append(lst[i])
i += 1
runs.append(new_run)
for run in runs:
sorted_runs.append(insertion_sort(run))
for run in sorted_runs:
sorted_array = merge(sorted_array, run)
return sorted_array
def main():
lst = [5, 9, 10, 3, -4, 5, 178, 92, 46, -18, 0, 7]
sorted_lst = tim_sort(lst)
print(sorted_lst)
if __name__ == "__main__":
main()
| -1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
|
## Arithmetic Analysis
* [Bisection](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/bisection.py)
* [Gaussian Elimination](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/gaussian_elimination.py)
* [In Static Equilibrium](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/in_static_equilibrium.py)
* [Intersection](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/intersection.py)
* [Lu Decomposition](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/lu_decomposition.py)
* [Newton Forward Interpolation](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/newton_forward_interpolation.py)
* [Newton Method](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/newton_method.py)
* [Newton Raphson](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/newton_raphson.py)
* [Secant Method](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/secant_method.py)
## Backtracking
* [All Combinations](https://github.com/TheAlgorithms/Python/blob/master/backtracking/all_combinations.py)
* [All Permutations](https://github.com/TheAlgorithms/Python/blob/master/backtracking/all_permutations.py)
* [All Subsequences](https://github.com/TheAlgorithms/Python/blob/master/backtracking/all_subsequences.py)
* [Coloring](https://github.com/TheAlgorithms/Python/blob/master/backtracking/coloring.py)
* [Hamiltonian Cycle](https://github.com/TheAlgorithms/Python/blob/master/backtracking/hamiltonian_cycle.py)
* [Knight Tour](https://github.com/TheAlgorithms/Python/blob/master/backtracking/knight_tour.py)
* [Minimax](https://github.com/TheAlgorithms/Python/blob/master/backtracking/minimax.py)
* [N Queens](https://github.com/TheAlgorithms/Python/blob/master/backtracking/n_queens.py)
* [N Queens Math](https://github.com/TheAlgorithms/Python/blob/master/backtracking/n_queens_math.py)
* [Rat In Maze](https://github.com/TheAlgorithms/Python/blob/master/backtracking/rat_in_maze.py)
* [Sudoku](https://github.com/TheAlgorithms/Python/blob/master/backtracking/sudoku.py)
* [Sum Of Subsets](https://github.com/TheAlgorithms/Python/blob/master/backtracking/sum_of_subsets.py)
## Bit Manipulation
* [Binary And Operator](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_and_operator.py)
* [Binary Count Setbits](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_count_setbits.py)
* [Binary Count Trailing Zeros](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_count_trailing_zeros.py)
* [Binary Or Operator](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_or_operator.py)
* [Binary Shifts](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_shifts.py)
* [Binary Twos Complement](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_twos_complement.py)
* [Binary Xor Operator](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_xor_operator.py)
* [Count Number Of One Bits](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/count_number_of_one_bits.py)
* [Reverse Bits](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/reverse_bits.py)
* [Single Bit Manipulation Operations](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/single_bit_manipulation_operations.py)
## Blockchain
* [Chinese Remainder Theorem](https://github.com/TheAlgorithms/Python/blob/master/blockchain/chinese_remainder_theorem.py)
* [Diophantine Equation](https://github.com/TheAlgorithms/Python/blob/master/blockchain/diophantine_equation.py)
* [Modular Division](https://github.com/TheAlgorithms/Python/blob/master/blockchain/modular_division.py)
## Boolean Algebra
* [Quine Mc Cluskey](https://github.com/TheAlgorithms/Python/blob/master/boolean_algebra/quine_mc_cluskey.py)
## Cellular Automata
* [Conways Game Of Life](https://github.com/TheAlgorithms/Python/blob/master/cellular_automata/conways_game_of_life.py)
* [Game Of Life](https://github.com/TheAlgorithms/Python/blob/master/cellular_automata/game_of_life.py)
* [One Dimensional](https://github.com/TheAlgorithms/Python/blob/master/cellular_automata/one_dimensional.py)
## Ciphers
* [A1Z26](https://github.com/TheAlgorithms/Python/blob/master/ciphers/a1z26.py)
* [Affine Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/affine_cipher.py)
* [Atbash](https://github.com/TheAlgorithms/Python/blob/master/ciphers/atbash.py)
* [Base16](https://github.com/TheAlgorithms/Python/blob/master/ciphers/base16.py)
* [Base32](https://github.com/TheAlgorithms/Python/blob/master/ciphers/base32.py)
* [Base64 Encoding](https://github.com/TheAlgorithms/Python/blob/master/ciphers/base64_encoding.py)
* [Base85](https://github.com/TheAlgorithms/Python/blob/master/ciphers/base85.py)
* [Beaufort Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/beaufort_cipher.py)
* [Brute Force Caesar Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/brute_force_caesar_cipher.py)
* [Caesar Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/caesar_cipher.py)
* [Cryptomath Module](https://github.com/TheAlgorithms/Python/blob/master/ciphers/cryptomath_module.py)
* [Decrypt Caesar With Chi Squared](https://github.com/TheAlgorithms/Python/blob/master/ciphers/decrypt_caesar_with_chi_squared.py)
* [Deterministic Miller Rabin](https://github.com/TheAlgorithms/Python/blob/master/ciphers/deterministic_miller_rabin.py)
* [Diffie](https://github.com/TheAlgorithms/Python/blob/master/ciphers/diffie.py)
* [Diffie Hellman](https://github.com/TheAlgorithms/Python/blob/master/ciphers/diffie_hellman.py)
* [Elgamal Key Generator](https://github.com/TheAlgorithms/Python/blob/master/ciphers/elgamal_key_generator.py)
* [Enigma Machine2](https://github.com/TheAlgorithms/Python/blob/master/ciphers/enigma_machine2.py)
* [Hill Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/hill_cipher.py)
* [Mixed Keyword Cypher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/mixed_keyword_cypher.py)
* [Mono Alphabetic Ciphers](https://github.com/TheAlgorithms/Python/blob/master/ciphers/mono_alphabetic_ciphers.py)
* [Morse Code Implementation](https://github.com/TheAlgorithms/Python/blob/master/ciphers/morse_code_implementation.py)
* [Onepad Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/onepad_cipher.py)
* [Playfair Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/playfair_cipher.py)
* [Porta Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/porta_cipher.py)
* [Rabin Miller](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rabin_miller.py)
* [Rail Fence Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rail_fence_cipher.py)
* [Rot13](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rot13.py)
* [Rsa Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rsa_cipher.py)
* [Rsa Factorization](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rsa_factorization.py)
* [Rsa Key Generator](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rsa_key_generator.py)
* [Shuffled Shift Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/shuffled_shift_cipher.py)
* [Simple Keyword Cypher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/simple_keyword_cypher.py)
* [Simple Substitution Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/simple_substitution_cipher.py)
* [Trafid Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/trafid_cipher.py)
* [Transposition Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/transposition_cipher.py)
* [Transposition Cipher Encrypt Decrypt File](https://github.com/TheAlgorithms/Python/blob/master/ciphers/transposition_cipher_encrypt_decrypt_file.py)
* [Vigenere Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/vigenere_cipher.py)
* [Xor Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/xor_cipher.py)
## Compression
* [Burrows Wheeler](https://github.com/TheAlgorithms/Python/blob/master/compression/burrows_wheeler.py)
* [Huffman](https://github.com/TheAlgorithms/Python/blob/master/compression/huffman.py)
* [Lempel Ziv](https://github.com/TheAlgorithms/Python/blob/master/compression/lempel_ziv.py)
* [Lempel Ziv Decompress](https://github.com/TheAlgorithms/Python/blob/master/compression/lempel_ziv_decompress.py)
* [Peak Signal To Noise Ratio](https://github.com/TheAlgorithms/Python/blob/master/compression/peak_signal_to_noise_ratio.py)
## Computer Vision
* [Harris Corner](https://github.com/TheAlgorithms/Python/blob/master/computer_vision/harris_corner.py)
* [Mean Threshold](https://github.com/TheAlgorithms/Python/blob/master/computer_vision/mean_threshold.py)
## Conversions
* [Binary To Decimal](https://github.com/TheAlgorithms/Python/blob/master/conversions/binary_to_decimal.py)
* [Binary To Octal](https://github.com/TheAlgorithms/Python/blob/master/conversions/binary_to_octal.py)
* [Decimal To Any](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_any.py)
* [Decimal To Binary](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_binary.py)
* [Decimal To Binary Recursion](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_binary_recursion.py)
* [Decimal To Hexadecimal](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_hexadecimal.py)
* [Decimal To Octal](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_octal.py)
* [Hex To Bin](https://github.com/TheAlgorithms/Python/blob/master/conversions/hex_to_bin.py)
* [Hexadecimal To Decimal](https://github.com/TheAlgorithms/Python/blob/master/conversions/hexadecimal_to_decimal.py)
* [Molecular Chemistry](https://github.com/TheAlgorithms/Python/blob/master/conversions/molecular_chemistry.py)
* [Octal To Decimal](https://github.com/TheAlgorithms/Python/blob/master/conversions/octal_to_decimal.py)
* [Prefix Conversions](https://github.com/TheAlgorithms/Python/blob/master/conversions/prefix_conversions.py)
* [Rgb Hsv Conversion](https://github.com/TheAlgorithms/Python/blob/master/conversions/rgb_hsv_conversion.py)
* [Roman Numerals](https://github.com/TheAlgorithms/Python/blob/master/conversions/roman_numerals.py)
* [Temperature Conversions](https://github.com/TheAlgorithms/Python/blob/master/conversions/temperature_conversions.py)
* [Weight Conversion](https://github.com/TheAlgorithms/Python/blob/master/conversions/weight_conversion.py)
## Data Structures
* Binary Tree
* [Avl Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/avl_tree.py)
* [Basic Binary Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/basic_binary_tree.py)
* [Binary Search Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/binary_search_tree.py)
* [Binary Search Tree Recursive](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/binary_search_tree_recursive.py)
* [Binary Tree Mirror](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/binary_tree_mirror.py)
* [Binary Tree Traversals](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/binary_tree_traversals.py)
* [Fenwick Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/fenwick_tree.py)
* [Lazy Segment Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/lazy_segment_tree.py)
* [Lowest Common Ancestor](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/lowest_common_ancestor.py)
* [Merge Two Binary Trees](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/merge_two_binary_trees.py)
* [Non Recursive Segment Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/non_recursive_segment_tree.py)
* [Number Of Possible Binary Trees](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/number_of_possible_binary_trees.py)
* [Red Black Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/red_black_tree.py)
* [Segment Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/segment_tree.py)
* [Segment Tree Other](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/segment_tree_other.py)
* [Treap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/treap.py)
* Disjoint Set
* [Alternate Disjoint Set](https://github.com/TheAlgorithms/Python/blob/master/data_structures/disjoint_set/alternate_disjoint_set.py)
* [Disjoint Set](https://github.com/TheAlgorithms/Python/blob/master/data_structures/disjoint_set/disjoint_set.py)
* Hashing
* [Double Hash](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/double_hash.py)
* [Hash Table](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/hash_table.py)
* [Hash Table With Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/hash_table_with_linked_list.py)
* Number Theory
* [Prime Numbers](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/number_theory/prime_numbers.py)
* [Quadratic Probing](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/quadratic_probing.py)
* Heap
* [Binomial Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/binomial_heap.py)
* [Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/heap.py)
* [Heap Generic](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/heap_generic.py)
* [Max Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/max_heap.py)
* [Min Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/min_heap.py)
* [Randomized Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/randomized_heap.py)
* [Skew Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/skew_heap.py)
* Linked List
* [Circular Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/circular_linked_list.py)
* [Deque Doubly](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/deque_doubly.py)
* [Doubly Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/doubly_linked_list.py)
* [Doubly Linked List Two](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/doubly_linked_list_two.py)
* [From Sequence](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/from_sequence.py)
* [Has Loop](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/has_loop.py)
* [Is Palindrome](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/is_palindrome.py)
* [Merge Two Lists](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/merge_two_lists.py)
* [Middle Element Of Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/middle_element_of_linked_list.py)
* [Print Reverse](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/print_reverse.py)
* [Singly Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/singly_linked_list.py)
* [Skip List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/skip_list.py)
* [Swap Nodes](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/swap_nodes.py)
* Queue
* [Circular Queue](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/circular_queue.py)
* [Double Ended Queue](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/double_ended_queue.py)
* [Linked Queue](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/linked_queue.py)
* [Priority Queue Using List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/priority_queue_using_list.py)
* [Queue On List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/queue_on_list.py)
* [Queue On Pseudo Stack](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/queue_on_pseudo_stack.py)
* Stacks
* [Balanced Parentheses](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/balanced_parentheses.py)
* [Dijkstras Two Stack Algorithm](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/dijkstras_two_stack_algorithm.py)
* [Evaluate Postfix Notations](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/evaluate_postfix_notations.py)
* [Infix To Postfix Conversion](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/infix_to_postfix_conversion.py)
* [Infix To Prefix Conversion](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/infix_to_prefix_conversion.py)
* [Linked Stack](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/linked_stack.py)
* [Next Greater Element](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/next_greater_element.py)
* [Postfix Evaluation](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/postfix_evaluation.py)
* [Prefix Evaluation](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/prefix_evaluation.py)
* [Stack](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/stack.py)
* [Stack Using Dll](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/stack_using_dll.py)
* [Stock Span Problem](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/stock_span_problem.py)
* Trie
* [Trie](https://github.com/TheAlgorithms/Python/blob/master/data_structures/trie/trie.py)
## Digital Image Processing
* [Change Brightness](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/change_brightness.py)
* [Change Contrast](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/change_contrast.py)
* [Convert To Negative](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/convert_to_negative.py)
* Dithering
* [Burkes](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/dithering/burkes.py)
* Edge Detection
* [Canny](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/edge_detection/canny.py)
* Filters
* [Bilateral Filter](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/bilateral_filter.py)
* [Convolve](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/convolve.py)
* [Gaussian Filter](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/gaussian_filter.py)
* [Median Filter](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/median_filter.py)
* [Sobel Filter](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/sobel_filter.py)
* Histogram Equalization
* [Histogram Stretch](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/histogram_equalization/histogram_stretch.py)
* [Index Calculation](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/index_calculation.py)
* Resize
* [Resize](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/resize/resize.py)
* Rotation
* [Rotation](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/rotation/rotation.py)
* [Sepia](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/sepia.py)
* [Test Digital Image Processing](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/test_digital_image_processing.py)
## Divide And Conquer
* [Closest Pair Of Points](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/closest_pair_of_points.py)
* [Convex Hull](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/convex_hull.py)
* [Heaps Algorithm](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/heaps_algorithm.py)
* [Heaps Algorithm Iterative](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/heaps_algorithm_iterative.py)
* [Inversions](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/inversions.py)
* [Kth Order Statistic](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/kth_order_statistic.py)
* [Max Difference Pair](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/max_difference_pair.py)
* [Max Subarray Sum](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/max_subarray_sum.py)
* [Mergesort](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/mergesort.py)
* [Peak](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/peak.py)
* [Power](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/power.py)
* [Strassen Matrix Multiplication](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/strassen_matrix_multiplication.py)
## Dynamic Programming
* [Abbreviation](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/abbreviation.py)
* [Bitmask](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/bitmask.py)
* [Climbing Stairs](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/climbing_stairs.py)
* [Edit Distance](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/edit_distance.py)
* [Factorial](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/factorial.py)
* [Fast Fibonacci](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/fast_fibonacci.py)
* [Fibonacci](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/fibonacci.py)
* [Floyd Warshall](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/floyd_warshall.py)
* [Fractional Knapsack](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/fractional_knapsack.py)
* [Fractional Knapsack 2](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/fractional_knapsack_2.py)
* [Integer Partition](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/integer_partition.py)
* [Iterating Through Submasks](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/iterating_through_submasks.py)
* [Knapsack](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/knapsack.py)
* [Longest Common Subsequence](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/longest_common_subsequence.py)
* [Longest Increasing Subsequence](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/longest_increasing_subsequence.py)
* [Longest Increasing Subsequence O(Nlogn)](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/longest_increasing_subsequence_o(nlogn).py)
* [Longest Sub Array](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/longest_sub_array.py)
* [Matrix Chain Order](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/matrix_chain_order.py)
* [Max Non Adjacent Sum](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/max_non_adjacent_sum.py)
* [Max Sub Array](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/max_sub_array.py)
* [Max Sum Contiguous Subsequence](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/max_sum_contiguous_subsequence.py)
* [Minimum Coin Change](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/minimum_coin_change.py)
* [Minimum Cost Path](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/minimum_cost_path.py)
* [Minimum Partition](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/minimum_partition.py)
* [Minimum Steps To One](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/minimum_steps_to_one.py)
* [Optimal Binary Search Tree](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/optimal_binary_search_tree.py)
* [Rod Cutting](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/rod_cutting.py)
* [Subset Generation](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/subset_generation.py)
* [Sum Of Subset](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/sum_of_subset.py)
## Electronics
* [Electric Power](https://github.com/TheAlgorithms/Python/blob/master/electronics/electric_power.py)
* [Ohms Law](https://github.com/TheAlgorithms/Python/blob/master/electronics/ohms_law.py)
## File Transfer
* [Receive File](https://github.com/TheAlgorithms/Python/blob/master/file_transfer/receive_file.py)
* [Send File](https://github.com/TheAlgorithms/Python/blob/master/file_transfer/send_file.py)
* Tests
* [Test Send File](https://github.com/TheAlgorithms/Python/blob/master/file_transfer/tests/test_send_file.py)
## Fractals
* [Koch Snowflake](https://github.com/TheAlgorithms/Python/blob/master/fractals/koch_snowflake.py)
* [Mandelbrot](https://github.com/TheAlgorithms/Python/blob/master/fractals/mandelbrot.py)
* [Sierpinski Triangle](https://github.com/TheAlgorithms/Python/blob/master/fractals/sierpinski_triangle.py)
## Fuzzy Logic
* [Fuzzy Operations](https://github.com/TheAlgorithms/Python/blob/master/fuzzy_logic/fuzzy_operations.py)
## Genetic Algorithm
* [Basic String](https://github.com/TheAlgorithms/Python/blob/master/genetic_algorithm/basic_string.py)
## Geodesy
* [Haversine Distance](https://github.com/TheAlgorithms/Python/blob/master/geodesy/haversine_distance.py)
* [Lamberts Ellipsoidal Distance](https://github.com/TheAlgorithms/Python/blob/master/geodesy/lamberts_ellipsoidal_distance.py)
## Graphics
* [Bezier Curve](https://github.com/TheAlgorithms/Python/blob/master/graphics/bezier_curve.py)
* [Vector3 For 2D Rendering](https://github.com/TheAlgorithms/Python/blob/master/graphics/vector3_for_2d_rendering.py)
## Graphs
* [A Star](https://github.com/TheAlgorithms/Python/blob/master/graphs/a_star.py)
* [Articulation Points](https://github.com/TheAlgorithms/Python/blob/master/graphs/articulation_points.py)
* [Basic Graphs](https://github.com/TheAlgorithms/Python/blob/master/graphs/basic_graphs.py)
* [Bellman Ford](https://github.com/TheAlgorithms/Python/blob/master/graphs/bellman_ford.py)
* [Bfs Shortest Path](https://github.com/TheAlgorithms/Python/blob/master/graphs/bfs_shortest_path.py)
* [Bfs Zero One Shortest Path](https://github.com/TheAlgorithms/Python/blob/master/graphs/bfs_zero_one_shortest_path.py)
* [Bidirectional A Star](https://github.com/TheAlgorithms/Python/blob/master/graphs/bidirectional_a_star.py)
* [Bidirectional Breadth First Search](https://github.com/TheAlgorithms/Python/blob/master/graphs/bidirectional_breadth_first_search.py)
* [Breadth First Search](https://github.com/TheAlgorithms/Python/blob/master/graphs/breadth_first_search.py)
* [Breadth First Search 2](https://github.com/TheAlgorithms/Python/blob/master/graphs/breadth_first_search_2.py)
* [Breadth First Search Shortest Path](https://github.com/TheAlgorithms/Python/blob/master/graphs/breadth_first_search_shortest_path.py)
* [Check Bipartite Graph Bfs](https://github.com/TheAlgorithms/Python/blob/master/graphs/check_bipartite_graph_bfs.py)
* [Check Bipartite Graph Dfs](https://github.com/TheAlgorithms/Python/blob/master/graphs/check_bipartite_graph_dfs.py)
* [Connected Components](https://github.com/TheAlgorithms/Python/blob/master/graphs/connected_components.py)
* [Depth First Search](https://github.com/TheAlgorithms/Python/blob/master/graphs/depth_first_search.py)
* [Depth First Search 2](https://github.com/TheAlgorithms/Python/blob/master/graphs/depth_first_search_2.py)
* [Dijkstra](https://github.com/TheAlgorithms/Python/blob/master/graphs/dijkstra.py)
* [Dijkstra 2](https://github.com/TheAlgorithms/Python/blob/master/graphs/dijkstra_2.py)
* [Dijkstra Algorithm](https://github.com/TheAlgorithms/Python/blob/master/graphs/dijkstra_algorithm.py)
* [Dinic](https://github.com/TheAlgorithms/Python/blob/master/graphs/dinic.py)
* [Directed And Undirected (Weighted) Graph](https://github.com/TheAlgorithms/Python/blob/master/graphs/directed_and_undirected_(weighted)_graph.py)
* [Edmonds Karp Multiple Source And Sink](https://github.com/TheAlgorithms/Python/blob/master/graphs/edmonds_karp_multiple_source_and_sink.py)
* [Eulerian Path And Circuit For Undirected Graph](https://github.com/TheAlgorithms/Python/blob/master/graphs/eulerian_path_and_circuit_for_undirected_graph.py)
* [Even Tree](https://github.com/TheAlgorithms/Python/blob/master/graphs/even_tree.py)
* [Finding Bridges](https://github.com/TheAlgorithms/Python/blob/master/graphs/finding_bridges.py)
* [Frequent Pattern Graph Miner](https://github.com/TheAlgorithms/Python/blob/master/graphs/frequent_pattern_graph_miner.py)
* [G Topological Sort](https://github.com/TheAlgorithms/Python/blob/master/graphs/g_topological_sort.py)
* [Gale Shapley Bigraph](https://github.com/TheAlgorithms/Python/blob/master/graphs/gale_shapley_bigraph.py)
* [Graph List](https://github.com/TheAlgorithms/Python/blob/master/graphs/graph_list.py)
* [Graph Matrix](https://github.com/TheAlgorithms/Python/blob/master/graphs/graph_matrix.py)
* [Graphs Floyd Warshall](https://github.com/TheAlgorithms/Python/blob/master/graphs/graphs_floyd_warshall.py)
* [Greedy Best First](https://github.com/TheAlgorithms/Python/blob/master/graphs/greedy_best_first.py)
* [Kahns Algorithm Long](https://github.com/TheAlgorithms/Python/blob/master/graphs/kahns_algorithm_long.py)
* [Kahns Algorithm Topo](https://github.com/TheAlgorithms/Python/blob/master/graphs/kahns_algorithm_topo.py)
* [Karger](https://github.com/TheAlgorithms/Python/blob/master/graphs/karger.py)
* [Markov Chain](https://github.com/TheAlgorithms/Python/blob/master/graphs/markov_chain.py)
* [Minimum Spanning Tree Boruvka](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_boruvka.py)
* [Minimum Spanning Tree Kruskal](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_kruskal.py)
* [Minimum Spanning Tree Kruskal2](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_kruskal2.py)
* [Minimum Spanning Tree Prims](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_prims.py)
* [Minimum Spanning Tree Prims2](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_prims2.py)
* [Multi Heuristic Astar](https://github.com/TheAlgorithms/Python/blob/master/graphs/multi_heuristic_astar.py)
* [Page Rank](https://github.com/TheAlgorithms/Python/blob/master/graphs/page_rank.py)
* [Prim](https://github.com/TheAlgorithms/Python/blob/master/graphs/prim.py)
* [Scc Kosaraju](https://github.com/TheAlgorithms/Python/blob/master/graphs/scc_kosaraju.py)
* [Strongly Connected Components](https://github.com/TheAlgorithms/Python/blob/master/graphs/strongly_connected_components.py)
* [Tarjans Scc](https://github.com/TheAlgorithms/Python/blob/master/graphs/tarjans_scc.py)
* Tests
* [Test Min Spanning Tree Kruskal](https://github.com/TheAlgorithms/Python/blob/master/graphs/tests/test_min_spanning_tree_kruskal.py)
* [Test Min Spanning Tree Prim](https://github.com/TheAlgorithms/Python/blob/master/graphs/tests/test_min_spanning_tree_prim.py)
## Hashes
* [Adler32](https://github.com/TheAlgorithms/Python/blob/master/hashes/adler32.py)
* [Chaos Machine](https://github.com/TheAlgorithms/Python/blob/master/hashes/chaos_machine.py)
* [Djb2](https://github.com/TheAlgorithms/Python/blob/master/hashes/djb2.py)
* [Enigma Machine](https://github.com/TheAlgorithms/Python/blob/master/hashes/enigma_machine.py)
* [Hamming Code](https://github.com/TheAlgorithms/Python/blob/master/hashes/hamming_code.py)
* [Md5](https://github.com/TheAlgorithms/Python/blob/master/hashes/md5.py)
* [Sdbm](https://github.com/TheAlgorithms/Python/blob/master/hashes/sdbm.py)
* [Sha1](https://github.com/TheAlgorithms/Python/blob/master/hashes/sha1.py)
## Knapsack
* [Greedy Knapsack](https://github.com/TheAlgorithms/Python/blob/master/knapsack/greedy_knapsack.py)
* [Knapsack](https://github.com/TheAlgorithms/Python/blob/master/knapsack/knapsack.py)
* Tests
* [Test Greedy Knapsack](https://github.com/TheAlgorithms/Python/blob/master/knapsack/tests/test_greedy_knapsack.py)
* [Test Knapsack](https://github.com/TheAlgorithms/Python/blob/master/knapsack/tests/test_knapsack.py)
## Linear Algebra
* Src
* [Conjugate Gradient](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/conjugate_gradient.py)
* [Lib](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/lib.py)
* [Polynom For Points](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/polynom_for_points.py)
* [Power Iteration](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/power_iteration.py)
* [Rayleigh Quotient](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/rayleigh_quotient.py)
* [Test Linear Algebra](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/test_linear_algebra.py)
* [Transformations 2D](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/transformations_2d.py)
## Machine Learning
* [Astar](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/astar.py)
* [Data Transformations](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/data_transformations.py)
* [Decision Tree](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/decision_tree.py)
* Forecasting
* [Run](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/forecasting/run.py)
* [Gaussian Naive Bayes](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gaussian_naive_bayes.py)
* [Gradient Boosting Regressor](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_boosting_regressor.py)
* [Gradient Descent](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_descent.py)
* [K Means Clust](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_means_clust.py)
* [K Nearest Neighbours](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_nearest_neighbours.py)
* [Knn Sklearn](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/knn_sklearn.py)
* [Linear Discriminant Analysis](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/linear_discriminant_analysis.py)
* [Linear Regression](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/linear_regression.py)
* [Logistic Regression](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/logistic_regression.py)
* Lstm
* [Lstm Prediction](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/lstm/lstm_prediction.py)
* [Multilayer Perceptron Classifier](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/multilayer_perceptron_classifier.py)
* [Polymonial Regression](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/polymonial_regression.py)
* [Random Forest Classifier](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/random_forest_classifier.py)
* [Random Forest Regressor](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/random_forest_regressor.py)
* [Scoring Functions](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/scoring_functions.py)
* [Sequential Minimum Optimization](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/sequential_minimum_optimization.py)
* [Similarity Search](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/similarity_search.py)
* [Support Vector Machines](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/support_vector_machines.py)
* [Word Frequency Functions](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/word_frequency_functions.py)
## Maths
* [3N Plus 1](https://github.com/TheAlgorithms/Python/blob/master/maths/3n_plus_1.py)
* [Abs](https://github.com/TheAlgorithms/Python/blob/master/maths/abs.py)
* [Abs Max](https://github.com/TheAlgorithms/Python/blob/master/maths/abs_max.py)
* [Abs Min](https://github.com/TheAlgorithms/Python/blob/master/maths/abs_min.py)
* [Add](https://github.com/TheAlgorithms/Python/blob/master/maths/add.py)
* [Aliquot Sum](https://github.com/TheAlgorithms/Python/blob/master/maths/aliquot_sum.py)
* [Allocation Number](https://github.com/TheAlgorithms/Python/blob/master/maths/allocation_number.py)
* [Area](https://github.com/TheAlgorithms/Python/blob/master/maths/area.py)
* [Area Under Curve](https://github.com/TheAlgorithms/Python/blob/master/maths/area_under_curve.py)
* [Armstrong Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/armstrong_numbers.py)
* [Average Mean](https://github.com/TheAlgorithms/Python/blob/master/maths/average_mean.py)
* [Average Median](https://github.com/TheAlgorithms/Python/blob/master/maths/average_median.py)
* [Average Mode](https://github.com/TheAlgorithms/Python/blob/master/maths/average_mode.py)
* [Bailey Borwein Plouffe](https://github.com/TheAlgorithms/Python/blob/master/maths/bailey_borwein_plouffe.py)
* [Basic Maths](https://github.com/TheAlgorithms/Python/blob/master/maths/basic_maths.py)
* [Binary Exp Mod](https://github.com/TheAlgorithms/Python/blob/master/maths/binary_exp_mod.py)
* [Binary Exponentiation](https://github.com/TheAlgorithms/Python/blob/master/maths/binary_exponentiation.py)
* [Binary Exponentiation 2](https://github.com/TheAlgorithms/Python/blob/master/maths/binary_exponentiation_2.py)
* [Binary Exponentiation 3](https://github.com/TheAlgorithms/Python/blob/master/maths/binary_exponentiation_3.py)
* [Binomial Coefficient](https://github.com/TheAlgorithms/Python/blob/master/maths/binomial_coefficient.py)
* [Binomial Distribution](https://github.com/TheAlgorithms/Python/blob/master/maths/binomial_distribution.py)
* [Bisection](https://github.com/TheAlgorithms/Python/blob/master/maths/bisection.py)
* [Ceil](https://github.com/TheAlgorithms/Python/blob/master/maths/ceil.py)
* [Chudnovsky Algorithm](https://github.com/TheAlgorithms/Python/blob/master/maths/chudnovsky_algorithm.py)
* [Collatz Sequence](https://github.com/TheAlgorithms/Python/blob/master/maths/collatz_sequence.py)
* [Combinations](https://github.com/TheAlgorithms/Python/blob/master/maths/combinations.py)
* [Decimal Isolate](https://github.com/TheAlgorithms/Python/blob/master/maths/decimal_isolate.py)
* [Entropy](https://github.com/TheAlgorithms/Python/blob/master/maths/entropy.py)
* [Euclidean Distance](https://github.com/TheAlgorithms/Python/blob/master/maths/euclidean_distance.py)
* [Euclidean Gcd](https://github.com/TheAlgorithms/Python/blob/master/maths/euclidean_gcd.py)
* [Euler Method](https://github.com/TheAlgorithms/Python/blob/master/maths/euler_method.py)
* [Eulers Totient](https://github.com/TheAlgorithms/Python/blob/master/maths/eulers_totient.py)
* [Extended Euclidean Algorithm](https://github.com/TheAlgorithms/Python/blob/master/maths/extended_euclidean_algorithm.py)
* [Factorial Iterative](https://github.com/TheAlgorithms/Python/blob/master/maths/factorial_iterative.py)
* [Factorial Python](https://github.com/TheAlgorithms/Python/blob/master/maths/factorial_python.py)
* [Factorial Recursive](https://github.com/TheAlgorithms/Python/blob/master/maths/factorial_recursive.py)
* [Factors](https://github.com/TheAlgorithms/Python/blob/master/maths/factors.py)
* [Fermat Little Theorem](https://github.com/TheAlgorithms/Python/blob/master/maths/fermat_little_theorem.py)
* [Fibonacci](https://github.com/TheAlgorithms/Python/blob/master/maths/fibonacci.py)
* [Fibonacci Sequence Recursion](https://github.com/TheAlgorithms/Python/blob/master/maths/fibonacci_sequence_recursion.py)
* [Find Max](https://github.com/TheAlgorithms/Python/blob/master/maths/find_max.py)
* [Find Max Recursion](https://github.com/TheAlgorithms/Python/blob/master/maths/find_max_recursion.py)
* [Find Min](https://github.com/TheAlgorithms/Python/blob/master/maths/find_min.py)
* [Find Min Recursion](https://github.com/TheAlgorithms/Python/blob/master/maths/find_min_recursion.py)
* [Floor](https://github.com/TheAlgorithms/Python/blob/master/maths/floor.py)
* [Gamma](https://github.com/TheAlgorithms/Python/blob/master/maths/gamma.py)
* [Gaussian](https://github.com/TheAlgorithms/Python/blob/master/maths/gaussian.py)
* [Greatest Common Divisor](https://github.com/TheAlgorithms/Python/blob/master/maths/greatest_common_divisor.py)
* [Greedy Coin Change](https://github.com/TheAlgorithms/Python/blob/master/maths/greedy_coin_change.py)
* [Hardy Ramanujanalgo](https://github.com/TheAlgorithms/Python/blob/master/maths/hardy_ramanujanalgo.py)
* [Integration By Simpson Approx](https://github.com/TheAlgorithms/Python/blob/master/maths/integration_by_simpson_approx.py)
* [Is Square Free](https://github.com/TheAlgorithms/Python/blob/master/maths/is_square_free.py)
* [Jaccard Similarity](https://github.com/TheAlgorithms/Python/blob/master/maths/jaccard_similarity.py)
* [Kadanes](https://github.com/TheAlgorithms/Python/blob/master/maths/kadanes.py)
* [Karatsuba](https://github.com/TheAlgorithms/Python/blob/master/maths/karatsuba.py)
* [Krishnamurthy Number](https://github.com/TheAlgorithms/Python/blob/master/maths/krishnamurthy_number.py)
* [Kth Lexicographic Permutation](https://github.com/TheAlgorithms/Python/blob/master/maths/kth_lexicographic_permutation.py)
* [Largest Of Very Large Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/largest_of_very_large_numbers.py)
* [Largest Subarray Sum](https://github.com/TheAlgorithms/Python/blob/master/maths/largest_subarray_sum.py)
* [Least Common Multiple](https://github.com/TheAlgorithms/Python/blob/master/maths/least_common_multiple.py)
* [Line Length](https://github.com/TheAlgorithms/Python/blob/master/maths/line_length.py)
* [Lucas Lehmer Primality Test](https://github.com/TheAlgorithms/Python/blob/master/maths/lucas_lehmer_primality_test.py)
* [Lucas Series](https://github.com/TheAlgorithms/Python/blob/master/maths/lucas_series.py)
* [Matrix Exponentiation](https://github.com/TheAlgorithms/Python/blob/master/maths/matrix_exponentiation.py)
* [Max Sum Sliding Window](https://github.com/TheAlgorithms/Python/blob/master/maths/max_sum_sliding_window.py)
* [Median Of Two Arrays](https://github.com/TheAlgorithms/Python/blob/master/maths/median_of_two_arrays.py)
* [Miller Rabin](https://github.com/TheAlgorithms/Python/blob/master/maths/miller_rabin.py)
* [Mobius Function](https://github.com/TheAlgorithms/Python/blob/master/maths/mobius_function.py)
* [Modular Exponential](https://github.com/TheAlgorithms/Python/blob/master/maths/modular_exponential.py)
* [Monte Carlo](https://github.com/TheAlgorithms/Python/blob/master/maths/monte_carlo.py)
* [Monte Carlo Dice](https://github.com/TheAlgorithms/Python/blob/master/maths/monte_carlo_dice.py)
* [Newton Raphson](https://github.com/TheAlgorithms/Python/blob/master/maths/newton_raphson.py)
* [Number Of Digits](https://github.com/TheAlgorithms/Python/blob/master/maths/number_of_digits.py)
* [Numerical Integration](https://github.com/TheAlgorithms/Python/blob/master/maths/numerical_integration.py)
* [Perfect Cube](https://github.com/TheAlgorithms/Python/blob/master/maths/perfect_cube.py)
* [Perfect Number](https://github.com/TheAlgorithms/Python/blob/master/maths/perfect_number.py)
* [Perfect Square](https://github.com/TheAlgorithms/Python/blob/master/maths/perfect_square.py)
* [Pi Monte Carlo Estimation](https://github.com/TheAlgorithms/Python/blob/master/maths/pi_monte_carlo_estimation.py)
* [Polynomial Evaluation](https://github.com/TheAlgorithms/Python/blob/master/maths/polynomial_evaluation.py)
* [Power Using Recursion](https://github.com/TheAlgorithms/Python/blob/master/maths/power_using_recursion.py)
* [Prime Check](https://github.com/TheAlgorithms/Python/blob/master/maths/prime_check.py)
* [Prime Factors](https://github.com/TheAlgorithms/Python/blob/master/maths/prime_factors.py)
* [Prime Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/prime_numbers.py)
* [Prime Sieve Eratosthenes](https://github.com/TheAlgorithms/Python/blob/master/maths/prime_sieve_eratosthenes.py)
* [Primelib](https://github.com/TheAlgorithms/Python/blob/master/maths/primelib.py)
* [Pythagoras](https://github.com/TheAlgorithms/Python/blob/master/maths/pythagoras.py)
* [Qr Decomposition](https://github.com/TheAlgorithms/Python/blob/master/maths/qr_decomposition.py)
* [Quadratic Equations Complex Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/quadratic_equations_complex_numbers.py)
* [Radians](https://github.com/TheAlgorithms/Python/blob/master/maths/radians.py)
* [Radix2 Fft](https://github.com/TheAlgorithms/Python/blob/master/maths/radix2_fft.py)
* [Relu](https://github.com/TheAlgorithms/Python/blob/master/maths/relu.py)
* [Runge Kutta](https://github.com/TheAlgorithms/Python/blob/master/maths/runge_kutta.py)
* [Segmented Sieve](https://github.com/TheAlgorithms/Python/blob/master/maths/segmented_sieve.py)
* Series
* [Arithmetic Mean](https://github.com/TheAlgorithms/Python/blob/master/maths/series/arithmetic_mean.py)
* [Geometric Mean](https://github.com/TheAlgorithms/Python/blob/master/maths/series/geometric_mean.py)
* [Geometric Series](https://github.com/TheAlgorithms/Python/blob/master/maths/series/geometric_series.py)
* [Harmonic Series](https://github.com/TheAlgorithms/Python/blob/master/maths/series/harmonic_series.py)
* [P Series](https://github.com/TheAlgorithms/Python/blob/master/maths/series/p_series.py)
* [Sieve Of Eratosthenes](https://github.com/TheAlgorithms/Python/blob/master/maths/sieve_of_eratosthenes.py)
* [Sigmoid](https://github.com/TheAlgorithms/Python/blob/master/maths/sigmoid.py)
* [Simpson Rule](https://github.com/TheAlgorithms/Python/blob/master/maths/simpson_rule.py)
* [Softmax](https://github.com/TheAlgorithms/Python/blob/master/maths/softmax.py)
* [Square Root](https://github.com/TheAlgorithms/Python/blob/master/maths/square_root.py)
* [Sum Of Arithmetic Series](https://github.com/TheAlgorithms/Python/blob/master/maths/sum_of_arithmetic_series.py)
* [Sum Of Digits](https://github.com/TheAlgorithms/Python/blob/master/maths/sum_of_digits.py)
* [Sum Of Geometric Progression](https://github.com/TheAlgorithms/Python/blob/master/maths/sum_of_geometric_progression.py)
* [Test Prime Check](https://github.com/TheAlgorithms/Python/blob/master/maths/test_prime_check.py)
* [Trapezoidal Rule](https://github.com/TheAlgorithms/Python/blob/master/maths/trapezoidal_rule.py)
* [Triplet Sum](https://github.com/TheAlgorithms/Python/blob/master/maths/triplet_sum.py)
* [Two Pointer](https://github.com/TheAlgorithms/Python/blob/master/maths/two_pointer.py)
* [Two Sum](https://github.com/TheAlgorithms/Python/blob/master/maths/two_sum.py)
* [Ugly Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/ugly_numbers.py)
* [Volume](https://github.com/TheAlgorithms/Python/blob/master/maths/volume.py)
* [Zellers Congruence](https://github.com/TheAlgorithms/Python/blob/master/maths/zellers_congruence.py)
## Matrix
* [Count Islands In Matrix](https://github.com/TheAlgorithms/Python/blob/master/matrix/count_islands_in_matrix.py)
* [Inverse Of Matrix](https://github.com/TheAlgorithms/Python/blob/master/matrix/inverse_of_matrix.py)
* [Matrix Class](https://github.com/TheAlgorithms/Python/blob/master/matrix/matrix_class.py)
* [Matrix Operation](https://github.com/TheAlgorithms/Python/blob/master/matrix/matrix_operation.py)
* [Nth Fibonacci Using Matrix Exponentiation](https://github.com/TheAlgorithms/Python/blob/master/matrix/nth_fibonacci_using_matrix_exponentiation.py)
* [Rotate Matrix](https://github.com/TheAlgorithms/Python/blob/master/matrix/rotate_matrix.py)
* [Searching In Sorted Matrix](https://github.com/TheAlgorithms/Python/blob/master/matrix/searching_in_sorted_matrix.py)
* [Sherman Morrison](https://github.com/TheAlgorithms/Python/blob/master/matrix/sherman_morrison.py)
* [Spiral Print](https://github.com/TheAlgorithms/Python/blob/master/matrix/spiral_print.py)
* Tests
* [Test Matrix Operation](https://github.com/TheAlgorithms/Python/blob/master/matrix/tests/test_matrix_operation.py)
## Networking Flow
* [Ford Fulkerson](https://github.com/TheAlgorithms/Python/blob/master/networking_flow/ford_fulkerson.py)
* [Minimum Cut](https://github.com/TheAlgorithms/Python/blob/master/networking_flow/minimum_cut.py)
## Neural Network
* [2 Hidden Layers Neural Network](https://github.com/TheAlgorithms/Python/blob/master/neural_network/2_hidden_layers_neural_network.py)
* [Back Propagation Neural Network](https://github.com/TheAlgorithms/Python/blob/master/neural_network/back_propagation_neural_network.py)
* [Convolution Neural Network](https://github.com/TheAlgorithms/Python/blob/master/neural_network/convolution_neural_network.py)
* [Perceptron](https://github.com/TheAlgorithms/Python/blob/master/neural_network/perceptron.py)
## Other
* [Activity Selection](https://github.com/TheAlgorithms/Python/blob/master/other/activity_selection.py)
* [Davis–Putnam–Logemann–Loveland](https://github.com/TheAlgorithms/Python/blob/master/other/davis–putnam–logemann–loveland.py)
* [Dijkstra Bankers Algorithm](https://github.com/TheAlgorithms/Python/blob/master/other/dijkstra_bankers_algorithm.py)
* [Doomsday](https://github.com/TheAlgorithms/Python/blob/master/other/doomsday.py)
* [Fischer Yates Shuffle](https://github.com/TheAlgorithms/Python/blob/master/other/fischer_yates_shuffle.py)
* [Gauss Easter](https://github.com/TheAlgorithms/Python/blob/master/other/gauss_easter.py)
* [Graham Scan](https://github.com/TheAlgorithms/Python/blob/master/other/graham_scan.py)
* [Greedy](https://github.com/TheAlgorithms/Python/blob/master/other/greedy.py)
* [Least Recently Used](https://github.com/TheAlgorithms/Python/blob/master/other/least_recently_used.py)
* [Lfu Cache](https://github.com/TheAlgorithms/Python/blob/master/other/lfu_cache.py)
* [Linear Congruential Generator](https://github.com/TheAlgorithms/Python/blob/master/other/linear_congruential_generator.py)
* [Lru Cache](https://github.com/TheAlgorithms/Python/blob/master/other/lru_cache.py)
* [Magicdiamondpattern](https://github.com/TheAlgorithms/Python/blob/master/other/magicdiamondpattern.py)
* [Nested Brackets](https://github.com/TheAlgorithms/Python/blob/master/other/nested_brackets.py)
* [Password Generator](https://github.com/TheAlgorithms/Python/blob/master/other/password_generator.py)
* [Scoring Algorithm](https://github.com/TheAlgorithms/Python/blob/master/other/scoring_algorithm.py)
* [Sdes](https://github.com/TheAlgorithms/Python/blob/master/other/sdes.py)
* [Tower Of Hanoi](https://github.com/TheAlgorithms/Python/blob/master/other/tower_of_hanoi.py)
## Physics
* [N Body Simulation](https://github.com/TheAlgorithms/Python/blob/master/physics/n_body_simulation.py)
## Project Euler
* Problem 001
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol3.py)
* [Sol4](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol4.py)
* [Sol5](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol5.py)
* [Sol6](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol6.py)
* [Sol7](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol7.py)
* Problem 002
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol3.py)
* [Sol4](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol4.py)
* [Sol5](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol5.py)
* Problem 003
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_003/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_003/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_003/sol3.py)
* Problem 004
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_004/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_004/sol2.py)
* Problem 005
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_005/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_005/sol2.py)
* Problem 006
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_006/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_006/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_006/sol3.py)
* [Sol4](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_006/sol4.py)
* Problem 007
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_007/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_007/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_007/sol3.py)
* Problem 008
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_008/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_008/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_008/sol3.py)
* Problem 009
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_009/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_009/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_009/sol3.py)
* Problem 010
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_010/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_010/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_010/sol3.py)
* Problem 011
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_011/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_011/sol2.py)
* Problem 012
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_012/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_012/sol2.py)
* Problem 013
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_013/sol1.py)
* Problem 014
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_014/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_014/sol2.py)
* Problem 015
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_015/sol1.py)
* Problem 016
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_016/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_016/sol2.py)
* Problem 017
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_017/sol1.py)
* Problem 018
* [Solution](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_018/solution.py)
* Problem 019
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_019/sol1.py)
* Problem 020
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_020/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_020/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_020/sol3.py)
* [Sol4](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_020/sol4.py)
* Problem 021
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_021/sol1.py)
* Problem 022
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_022/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_022/sol2.py)
* Problem 023
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_023/sol1.py)
* Problem 024
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_024/sol1.py)
* Problem 025
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_025/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_025/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_025/sol3.py)
* Problem 026
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_026/sol1.py)
* Problem 027
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_027/sol1.py)
* Problem 028
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_028/sol1.py)
* Problem 029
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_029/sol1.py)
* Problem 030
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_030/sol1.py)
* Problem 031
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_031/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_031/sol2.py)
* Problem 032
* [Sol32](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_032/sol32.py)
* Problem 033
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_033/sol1.py)
* Problem 034
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_034/sol1.py)
* Problem 035
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_035/sol1.py)
* Problem 036
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_036/sol1.py)
* Problem 037
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_037/sol1.py)
* Problem 038
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_038/sol1.py)
* Problem 039
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_039/sol1.py)
* Problem 040
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_040/sol1.py)
* Problem 041
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_041/sol1.py)
* Problem 042
* [Solution42](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_042/solution42.py)
* Problem 043
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_043/sol1.py)
* Problem 044
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_044/sol1.py)
* Problem 045
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_045/sol1.py)
* Problem 046
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_046/sol1.py)
* Problem 047
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_047/sol1.py)
* Problem 048
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_048/sol1.py)
* Problem 049
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_049/sol1.py)
* Problem 050
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_050/sol1.py)
* Problem 051
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_051/sol1.py)
* Problem 052
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_052/sol1.py)
* Problem 053
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_053/sol1.py)
* Problem 054
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_054/sol1.py)
* [Test Poker Hand](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_054/test_poker_hand.py)
* Problem 055
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_055/sol1.py)
* Problem 056
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_056/sol1.py)
* Problem 057
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_057/sol1.py)
* Problem 058
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_058/sol1.py)
* Problem 059
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_059/sol1.py)
* Problem 062
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_062/sol1.py)
* Problem 063
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_063/sol1.py)
* Problem 064
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_064/sol1.py)
* Problem 065
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_065/sol1.py)
* Problem 067
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_067/sol1.py)
* Problem 069
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_069/sol1.py)
* Problem 070
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_070/sol1.py)
* Problem 071
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_071/sol1.py)
* Problem 072
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_072/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_072/sol2.py)
* Problem 074
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_074/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_074/sol2.py)
* Problem 075
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_075/sol1.py)
* Problem 076
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_076/sol1.py)
* Problem 077
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_077/sol1.py)
* Problem 080
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_080/sol1.py)
* Problem 081
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_081/sol1.py)
* Problem 085
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_085/sol1.py)
* Problem 086
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_086/sol1.py)
* Problem 087
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_087/sol1.py)
* Problem 089
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_089/sol1.py)
* Problem 091
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_091/sol1.py)
* Problem 097
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_097/sol1.py)
* Problem 099
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_099/sol1.py)
* Problem 101
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_101/sol1.py)
* Problem 102
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_102/sol1.py)
* Problem 107
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_107/sol1.py)
* Problem 109
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_109/sol1.py)
* Problem 112
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_112/sol1.py)
* Problem 113
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_113/sol1.py)
* Problem 119
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_119/sol1.py)
* Problem 120
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_120/sol1.py)
* Problem 121
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_121/sol1.py)
* Problem 123
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_123/sol1.py)
* Problem 125
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_125/sol1.py)
* Problem 129
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_129/sol1.py)
* Problem 135
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_135/sol1.py)
* Problem 173
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_173/sol1.py)
* Problem 174
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_174/sol1.py)
* Problem 180
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_180/sol1.py)
* Problem 188
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_188/sol1.py)
* Problem 191
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_191/sol1.py)
* Problem 203
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_203/sol1.py)
* Problem 206
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_206/sol1.py)
* Problem 207
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_207/sol1.py)
* Problem 234
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_234/sol1.py)
* Problem 301
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_301/sol1.py)
* Problem 551
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_551/sol1.py)
## Quantum
* [Deutsch Jozsa](https://github.com/TheAlgorithms/Python/blob/master/quantum/deutsch_jozsa.py)
* [Half Adder](https://github.com/TheAlgorithms/Python/blob/master/quantum/half_adder.py)
* [Not Gate](https://github.com/TheAlgorithms/Python/blob/master/quantum/not_gate.py)
* [Quantum Entanglement](https://github.com/TheAlgorithms/Python/blob/master/quantum/quantum_entanglement.py)
* [Ripple Adder Classic](https://github.com/TheAlgorithms/Python/blob/master/quantum/ripple_adder_classic.py)
* [Single Qubit Measure](https://github.com/TheAlgorithms/Python/blob/master/quantum/single_qubit_measure.py)
## Scheduling
* [First Come First Served](https://github.com/TheAlgorithms/Python/blob/master/scheduling/first_come_first_served.py)
* [Round Robin](https://github.com/TheAlgorithms/Python/blob/master/scheduling/round_robin.py)
* [Shortest Job First](https://github.com/TheAlgorithms/Python/blob/master/scheduling/shortest_job_first.py)
## Searches
* [Binary Search](https://github.com/TheAlgorithms/Python/blob/master/searches/binary_search.py)
* [Binary Tree Traversal](https://github.com/TheAlgorithms/Python/blob/master/searches/binary_tree_traversal.py)
* [Double Linear Search](https://github.com/TheAlgorithms/Python/blob/master/searches/double_linear_search.py)
* [Double Linear Search Recursion](https://github.com/TheAlgorithms/Python/blob/master/searches/double_linear_search_recursion.py)
* [Fibonacci Search](https://github.com/TheAlgorithms/Python/blob/master/searches/fibonacci_search.py)
* [Hill Climbing](https://github.com/TheAlgorithms/Python/blob/master/searches/hill_climbing.py)
* [Interpolation Search](https://github.com/TheAlgorithms/Python/blob/master/searches/interpolation_search.py)
* [Jump Search](https://github.com/TheAlgorithms/Python/blob/master/searches/jump_search.py)
* [Linear Search](https://github.com/TheAlgorithms/Python/blob/master/searches/linear_search.py)
* [Quick Select](https://github.com/TheAlgorithms/Python/blob/master/searches/quick_select.py)
* [Sentinel Linear Search](https://github.com/TheAlgorithms/Python/blob/master/searches/sentinel_linear_search.py)
* [Simple Binary Search](https://github.com/TheAlgorithms/Python/blob/master/searches/simple_binary_search.py)
* [Simulated Annealing](https://github.com/TheAlgorithms/Python/blob/master/searches/simulated_annealing.py)
* [Tabu Search](https://github.com/TheAlgorithms/Python/blob/master/searches/tabu_search.py)
* [Ternary Search](https://github.com/TheAlgorithms/Python/blob/master/searches/ternary_search.py)
## Sorts
* [Bead Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bead_sort.py)
* [Bitonic Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bitonic_sort.py)
* [Bogo Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bogo_sort.py)
* [Bubble Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bubble_sort.py)
* [Bucket Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bucket_sort.py)
* [Cocktail Shaker Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/cocktail_shaker_sort.py)
* [Comb Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/comb_sort.py)
* [Counting Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/counting_sort.py)
* [Cycle Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/cycle_sort.py)
* [Double Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/double_sort.py)
* [External Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/external_sort.py)
* [Gnome Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/gnome_sort.py)
* [Heap Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/heap_sort.py)
* [Insertion Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/insertion_sort.py)
* [Intro Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/intro_sort.py)
* [Iterative Merge Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/iterative_merge_sort.py)
* [Merge Insertion Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/merge_insertion_sort.py)
* [Merge Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/merge_sort.py)
* [Msd Radix Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/msd_radix_sort.py)
* [Natural Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/natural_sort.py)
* [Odd Even Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/odd_even_sort.py)
* [Odd Even Transposition Parallel](https://github.com/TheAlgorithms/Python/blob/master/sorts/odd_even_transposition_parallel.py)
* [Odd Even Transposition Single Threaded](https://github.com/TheAlgorithms/Python/blob/master/sorts/odd_even_transposition_single_threaded.py)
* [Pancake Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/pancake_sort.py)
* [Patience Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/patience_sort.py)
* [Pigeon Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/pigeon_sort.py)
* [Pigeonhole Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/pigeonhole_sort.py)
* [Quick Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/quick_sort.py)
* [Quick Sort 3 Partition](https://github.com/TheAlgorithms/Python/blob/master/sorts/quick_sort_3_partition.py)
* [Radix Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/radix_sort.py)
* [Random Normal Distribution Quicksort](https://github.com/TheAlgorithms/Python/blob/master/sorts/random_normal_distribution_quicksort.py)
* [Random Pivot Quick Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/random_pivot_quick_sort.py)
* [Recursive Bubble Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/recursive_bubble_sort.py)
* [Recursive Insertion Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/recursive_insertion_sort.py)
* [Recursive Mergesort Array](https://github.com/TheAlgorithms/Python/blob/master/sorts/recursive_mergesort_array.py)
* [Recursive Quick Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/recursive_quick_sort.py)
* [Selection Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/selection_sort.py)
* [Shell Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/shell_sort.py)
* [Slowsort](https://github.com/TheAlgorithms/Python/blob/master/sorts/slowsort.py)
* [Stooge Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/stooge_sort.py)
* [Strand Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/strand_sort.py)
* [Tim Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/tim_sort.py)
* [Topological Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/topological_sort.py)
* [Tree Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/tree_sort.py)
* [Unknown Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/unknown_sort.py)
* [Wiggle Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/wiggle_sort.py)
## Strings
* [Aho Corasick](https://github.com/TheAlgorithms/Python/blob/master/strings/aho_corasick.py)
* [Anagrams](https://github.com/TheAlgorithms/Python/blob/master/strings/anagrams.py)
* [Autocomplete Using Trie](https://github.com/TheAlgorithms/Python/blob/master/strings/autocomplete_using_trie.py)
* [Boyer Moore Search](https://github.com/TheAlgorithms/Python/blob/master/strings/boyer_moore_search.py)
* [Can String Be Rearranged As Palindrome](https://github.com/TheAlgorithms/Python/blob/master/strings/can_string_be_rearranged_as_palindrome.py)
* [Capitalize](https://github.com/TheAlgorithms/Python/blob/master/strings/capitalize.py)
* [Check Anagrams](https://github.com/TheAlgorithms/Python/blob/master/strings/check_anagrams.py)
* [Check Pangram](https://github.com/TheAlgorithms/Python/blob/master/strings/check_pangram.py)
* [Detecting English Programmatically](https://github.com/TheAlgorithms/Python/blob/master/strings/detecting_english_programmatically.py)
* [Frequency Finder](https://github.com/TheAlgorithms/Python/blob/master/strings/frequency_finder.py)
* [Is Palindrome](https://github.com/TheAlgorithms/Python/blob/master/strings/is_palindrome.py)
* [Jaro Winkler](https://github.com/TheAlgorithms/Python/blob/master/strings/jaro_winkler.py)
* [Knuth Morris Pratt](https://github.com/TheAlgorithms/Python/blob/master/strings/knuth_morris_pratt.py)
* [Levenshtein Distance](https://github.com/TheAlgorithms/Python/blob/master/strings/levenshtein_distance.py)
* [Lower](https://github.com/TheAlgorithms/Python/blob/master/strings/lower.py)
* [Manacher](https://github.com/TheAlgorithms/Python/blob/master/strings/manacher.py)
* [Min Cost String Conversion](https://github.com/TheAlgorithms/Python/blob/master/strings/min_cost_string_conversion.py)
* [Naive String Search](https://github.com/TheAlgorithms/Python/blob/master/strings/naive_string_search.py)
* [Palindrome](https://github.com/TheAlgorithms/Python/blob/master/strings/palindrome.py)
* [Prefix Function](https://github.com/TheAlgorithms/Python/blob/master/strings/prefix_function.py)
* [Rabin Karp](https://github.com/TheAlgorithms/Python/blob/master/strings/rabin_karp.py)
* [Remove Duplicate](https://github.com/TheAlgorithms/Python/blob/master/strings/remove_duplicate.py)
* [Reverse Letters](https://github.com/TheAlgorithms/Python/blob/master/strings/reverse_letters.py)
* [Reverse Words](https://github.com/TheAlgorithms/Python/blob/master/strings/reverse_words.py)
* [Split](https://github.com/TheAlgorithms/Python/blob/master/strings/split.py)
* [Swap Case](https://github.com/TheAlgorithms/Python/blob/master/strings/swap_case.py)
* [Upper](https://github.com/TheAlgorithms/Python/blob/master/strings/upper.py)
* [Word Occurrence](https://github.com/TheAlgorithms/Python/blob/master/strings/word_occurrence.py)
* [Word Patterns](https://github.com/TheAlgorithms/Python/blob/master/strings/word_patterns.py)
* [Z Function](https://github.com/TheAlgorithms/Python/blob/master/strings/z_function.py)
## Web Programming
* [Co2 Emission](https://github.com/TheAlgorithms/Python/blob/master/web_programming/co2_emission.py)
* [Covid Stats Via Xpath](https://github.com/TheAlgorithms/Python/blob/master/web_programming/covid_stats_via_xpath.py)
* [Crawl Google Results](https://github.com/TheAlgorithms/Python/blob/master/web_programming/crawl_google_results.py)
* [Crawl Google Scholar Citation](https://github.com/TheAlgorithms/Python/blob/master/web_programming/crawl_google_scholar_citation.py)
* [Currency Converter](https://github.com/TheAlgorithms/Python/blob/master/web_programming/currency_converter.py)
* [Current Stock Price](https://github.com/TheAlgorithms/Python/blob/master/web_programming/current_stock_price.py)
* [Current Weather](https://github.com/TheAlgorithms/Python/blob/master/web_programming/current_weather.py)
* [Daily Horoscope](https://github.com/TheAlgorithms/Python/blob/master/web_programming/daily_horoscope.py)
* [Emails From Url](https://github.com/TheAlgorithms/Python/blob/master/web_programming/emails_from_url.py)
* [Fetch Bbc News](https://github.com/TheAlgorithms/Python/blob/master/web_programming/fetch_bbc_news.py)
* [Fetch Github Info](https://github.com/TheAlgorithms/Python/blob/master/web_programming/fetch_github_info.py)
* [Fetch Jobs](https://github.com/TheAlgorithms/Python/blob/master/web_programming/fetch_jobs.py)
* [Get Imdb Top 250 Movies Csv](https://github.com/TheAlgorithms/Python/blob/master/web_programming/get_imdb_top_250_movies_csv.py)
* [Get Imdbtop](https://github.com/TheAlgorithms/Python/blob/master/web_programming/get_imdbtop.py)
* [Instagram Crawler](https://github.com/TheAlgorithms/Python/blob/master/web_programming/instagram_crawler.py)
* [Instagram Pic](https://github.com/TheAlgorithms/Python/blob/master/web_programming/instagram_pic.py)
* [Instagram Video](https://github.com/TheAlgorithms/Python/blob/master/web_programming/instagram_video.py)
* [Recaptcha Verification](https://github.com/TheAlgorithms/Python/blob/master/web_programming/recaptcha_verification.py)
* [Slack Message](https://github.com/TheAlgorithms/Python/blob/master/web_programming/slack_message.py)
* [Test Fetch Github Info](https://github.com/TheAlgorithms/Python/blob/master/web_programming/test_fetch_github_info.py)
* [World Covid19 Stats](https://github.com/TheAlgorithms/Python/blob/master/web_programming/world_covid19_stats.py)
|
## Arithmetic Analysis
* [Bisection](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/bisection.py)
* [Gaussian Elimination](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/gaussian_elimination.py)
* [In Static Equilibrium](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/in_static_equilibrium.py)
* [Intersection](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/intersection.py)
* [Lu Decomposition](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/lu_decomposition.py)
* [Newton Forward Interpolation](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/newton_forward_interpolation.py)
* [Newton Method](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/newton_method.py)
* [Newton Raphson](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/newton_raphson.py)
* [Secant Method](https://github.com/TheAlgorithms/Python/blob/master/arithmetic_analysis/secant_method.py)
## Backtracking
* [All Combinations](https://github.com/TheAlgorithms/Python/blob/master/backtracking/all_combinations.py)
* [All Permutations](https://github.com/TheAlgorithms/Python/blob/master/backtracking/all_permutations.py)
* [All Subsequences](https://github.com/TheAlgorithms/Python/blob/master/backtracking/all_subsequences.py)
* [Coloring](https://github.com/TheAlgorithms/Python/blob/master/backtracking/coloring.py)
* [Hamiltonian Cycle](https://github.com/TheAlgorithms/Python/blob/master/backtracking/hamiltonian_cycle.py)
* [Knight Tour](https://github.com/TheAlgorithms/Python/blob/master/backtracking/knight_tour.py)
* [Minimax](https://github.com/TheAlgorithms/Python/blob/master/backtracking/minimax.py)
* [N Queens](https://github.com/TheAlgorithms/Python/blob/master/backtracking/n_queens.py)
* [N Queens Math](https://github.com/TheAlgorithms/Python/blob/master/backtracking/n_queens_math.py)
* [Rat In Maze](https://github.com/TheAlgorithms/Python/blob/master/backtracking/rat_in_maze.py)
* [Sudoku](https://github.com/TheAlgorithms/Python/blob/master/backtracking/sudoku.py)
* [Sum Of Subsets](https://github.com/TheAlgorithms/Python/blob/master/backtracking/sum_of_subsets.py)
## Bit Manipulation
* [Binary And Operator](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_and_operator.py)
* [Binary Count Setbits](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_count_setbits.py)
* [Binary Count Trailing Zeros](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_count_trailing_zeros.py)
* [Binary Or Operator](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_or_operator.py)
* [Binary Shifts](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_shifts.py)
* [Binary Twos Complement](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_twos_complement.py)
* [Binary Xor Operator](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/binary_xor_operator.py)
* [Count Number Of One Bits](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/count_number_of_one_bits.py)
* [Reverse Bits](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/reverse_bits.py)
* [Single Bit Manipulation Operations](https://github.com/TheAlgorithms/Python/blob/master/bit_manipulation/single_bit_manipulation_operations.py)
## Blockchain
* [Chinese Remainder Theorem](https://github.com/TheAlgorithms/Python/blob/master/blockchain/chinese_remainder_theorem.py)
* [Diophantine Equation](https://github.com/TheAlgorithms/Python/blob/master/blockchain/diophantine_equation.py)
* [Modular Division](https://github.com/TheAlgorithms/Python/blob/master/blockchain/modular_division.py)
## Boolean Algebra
* [Quine Mc Cluskey](https://github.com/TheAlgorithms/Python/blob/master/boolean_algebra/quine_mc_cluskey.py)
## Cellular Automata
* [Conways Game Of Life](https://github.com/TheAlgorithms/Python/blob/master/cellular_automata/conways_game_of_life.py)
* [Game Of Life](https://github.com/TheAlgorithms/Python/blob/master/cellular_automata/game_of_life.py)
* [One Dimensional](https://github.com/TheAlgorithms/Python/blob/master/cellular_automata/one_dimensional.py)
## Ciphers
* [A1Z26](https://github.com/TheAlgorithms/Python/blob/master/ciphers/a1z26.py)
* [Affine Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/affine_cipher.py)
* [Atbash](https://github.com/TheAlgorithms/Python/blob/master/ciphers/atbash.py)
* [Base16](https://github.com/TheAlgorithms/Python/blob/master/ciphers/base16.py)
* [Base32](https://github.com/TheAlgorithms/Python/blob/master/ciphers/base32.py)
* [Base64 Encoding](https://github.com/TheAlgorithms/Python/blob/master/ciphers/base64_encoding.py)
* [Base85](https://github.com/TheAlgorithms/Python/blob/master/ciphers/base85.py)
* [Beaufort Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/beaufort_cipher.py)
* [Brute Force Caesar Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/brute_force_caesar_cipher.py)
* [Caesar Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/caesar_cipher.py)
* [Cryptomath Module](https://github.com/TheAlgorithms/Python/blob/master/ciphers/cryptomath_module.py)
* [Decrypt Caesar With Chi Squared](https://github.com/TheAlgorithms/Python/blob/master/ciphers/decrypt_caesar_with_chi_squared.py)
* [Deterministic Miller Rabin](https://github.com/TheAlgorithms/Python/blob/master/ciphers/deterministic_miller_rabin.py)
* [Diffie](https://github.com/TheAlgorithms/Python/blob/master/ciphers/diffie.py)
* [Diffie Hellman](https://github.com/TheAlgorithms/Python/blob/master/ciphers/diffie_hellman.py)
* [Elgamal Key Generator](https://github.com/TheAlgorithms/Python/blob/master/ciphers/elgamal_key_generator.py)
* [Enigma Machine2](https://github.com/TheAlgorithms/Python/blob/master/ciphers/enigma_machine2.py)
* [Hill Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/hill_cipher.py)
* [Mixed Keyword Cypher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/mixed_keyword_cypher.py)
* [Mono Alphabetic Ciphers](https://github.com/TheAlgorithms/Python/blob/master/ciphers/mono_alphabetic_ciphers.py)
* [Morse Code Implementation](https://github.com/TheAlgorithms/Python/blob/master/ciphers/morse_code_implementation.py)
* [Onepad Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/onepad_cipher.py)
* [Playfair Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/playfair_cipher.py)
* [Porta Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/porta_cipher.py)
* [Rabin Miller](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rabin_miller.py)
* [Rail Fence Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rail_fence_cipher.py)
* [Rot13](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rot13.py)
* [Rsa Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rsa_cipher.py)
* [Rsa Factorization](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rsa_factorization.py)
* [Rsa Key Generator](https://github.com/TheAlgorithms/Python/blob/master/ciphers/rsa_key_generator.py)
* [Shuffled Shift Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/shuffled_shift_cipher.py)
* [Simple Keyword Cypher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/simple_keyword_cypher.py)
* [Simple Substitution Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/simple_substitution_cipher.py)
* [Trafid Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/trafid_cipher.py)
* [Transposition Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/transposition_cipher.py)
* [Transposition Cipher Encrypt Decrypt File](https://github.com/TheAlgorithms/Python/blob/master/ciphers/transposition_cipher_encrypt_decrypt_file.py)
* [Vigenere Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/vigenere_cipher.py)
* [Xor Cipher](https://github.com/TheAlgorithms/Python/blob/master/ciphers/xor_cipher.py)
## Compression
* [Burrows Wheeler](https://github.com/TheAlgorithms/Python/blob/master/compression/burrows_wheeler.py)
* [Huffman](https://github.com/TheAlgorithms/Python/blob/master/compression/huffman.py)
* [Lempel Ziv](https://github.com/TheAlgorithms/Python/blob/master/compression/lempel_ziv.py)
* [Lempel Ziv Decompress](https://github.com/TheAlgorithms/Python/blob/master/compression/lempel_ziv_decompress.py)
* [Peak Signal To Noise Ratio](https://github.com/TheAlgorithms/Python/blob/master/compression/peak_signal_to_noise_ratio.py)
## Computer Vision
* [Harris Corner](https://github.com/TheAlgorithms/Python/blob/master/computer_vision/harris_corner.py)
* [Mean Threshold](https://github.com/TheAlgorithms/Python/blob/master/computer_vision/mean_threshold.py)
## Conversions
* [Binary To Decimal](https://github.com/TheAlgorithms/Python/blob/master/conversions/binary_to_decimal.py)
* [Binary To Octal](https://github.com/TheAlgorithms/Python/blob/master/conversions/binary_to_octal.py)
* [Decimal To Any](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_any.py)
* [Decimal To Binary](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_binary.py)
* [Decimal To Binary Recursion](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_binary_recursion.py)
* [Decimal To Hexadecimal](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_hexadecimal.py)
* [Decimal To Octal](https://github.com/TheAlgorithms/Python/blob/master/conversions/decimal_to_octal.py)
* [Hex To Bin](https://github.com/TheAlgorithms/Python/blob/master/conversions/hex_to_bin.py)
* [Hexadecimal To Decimal](https://github.com/TheAlgorithms/Python/blob/master/conversions/hexadecimal_to_decimal.py)
* [Molecular Chemistry](https://github.com/TheAlgorithms/Python/blob/master/conversions/molecular_chemistry.py)
* [Octal To Decimal](https://github.com/TheAlgorithms/Python/blob/master/conversions/octal_to_decimal.py)
* [Prefix Conversions](https://github.com/TheAlgorithms/Python/blob/master/conversions/prefix_conversions.py)
* [Rgb Hsv Conversion](https://github.com/TheAlgorithms/Python/blob/master/conversions/rgb_hsv_conversion.py)
* [Roman Numerals](https://github.com/TheAlgorithms/Python/blob/master/conversions/roman_numerals.py)
* [Temperature Conversions](https://github.com/TheAlgorithms/Python/blob/master/conversions/temperature_conversions.py)
* [Weight Conversion](https://github.com/TheAlgorithms/Python/blob/master/conversions/weight_conversion.py)
## Data Structures
* Binary Tree
* [Avl Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/avl_tree.py)
* [Basic Binary Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/basic_binary_tree.py)
* [Binary Search Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/binary_search_tree.py)
* [Binary Search Tree Recursive](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/binary_search_tree_recursive.py)
* [Binary Tree Mirror](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/binary_tree_mirror.py)
* [Binary Tree Traversals](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/binary_tree_traversals.py)
* [Fenwick Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/fenwick_tree.py)
* [Lazy Segment Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/lazy_segment_tree.py)
* [Lowest Common Ancestor](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/lowest_common_ancestor.py)
* [Merge Two Binary Trees](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/merge_two_binary_trees.py)
* [Non Recursive Segment Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/non_recursive_segment_tree.py)
* [Number Of Possible Binary Trees](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/number_of_possible_binary_trees.py)
* [Red Black Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/red_black_tree.py)
* [Segment Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/segment_tree.py)
* [Segment Tree Other](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/segment_tree_other.py)
* [Treap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/treap.py)
* [Wavelet Tree](https://github.com/TheAlgorithms/Python/blob/master/data_structures/binary_tree/wavelet_tree.py)
* Disjoint Set
* [Alternate Disjoint Set](https://github.com/TheAlgorithms/Python/blob/master/data_structures/disjoint_set/alternate_disjoint_set.py)
* [Disjoint Set](https://github.com/TheAlgorithms/Python/blob/master/data_structures/disjoint_set/disjoint_set.py)
* Hashing
* [Double Hash](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/double_hash.py)
* [Hash Table](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/hash_table.py)
* [Hash Table With Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/hash_table_with_linked_list.py)
* Number Theory
* [Prime Numbers](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/number_theory/prime_numbers.py)
* [Quadratic Probing](https://github.com/TheAlgorithms/Python/blob/master/data_structures/hashing/quadratic_probing.py)
* Heap
* [Binomial Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/binomial_heap.py)
* [Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/heap.py)
* [Heap Generic](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/heap_generic.py)
* [Max Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/max_heap.py)
* [Min Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/min_heap.py)
* [Randomized Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/randomized_heap.py)
* [Skew Heap](https://github.com/TheAlgorithms/Python/blob/master/data_structures/heap/skew_heap.py)
* Linked List
* [Circular Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/circular_linked_list.py)
* [Deque Doubly](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/deque_doubly.py)
* [Doubly Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/doubly_linked_list.py)
* [Doubly Linked List Two](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/doubly_linked_list_two.py)
* [From Sequence](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/from_sequence.py)
* [Has Loop](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/has_loop.py)
* [Is Palindrome](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/is_palindrome.py)
* [Merge Two Lists](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/merge_two_lists.py)
* [Middle Element Of Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/middle_element_of_linked_list.py)
* [Print Reverse](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/print_reverse.py)
* [Singly Linked List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/singly_linked_list.py)
* [Skip List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/skip_list.py)
* [Swap Nodes](https://github.com/TheAlgorithms/Python/blob/master/data_structures/linked_list/swap_nodes.py)
* Queue
* [Circular Queue](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/circular_queue.py)
* [Double Ended Queue](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/double_ended_queue.py)
* [Linked Queue](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/linked_queue.py)
* [Priority Queue Using List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/priority_queue_using_list.py)
* [Queue On List](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/queue_on_list.py)
* [Queue On Pseudo Stack](https://github.com/TheAlgorithms/Python/blob/master/data_structures/queue/queue_on_pseudo_stack.py)
* Stacks
* [Balanced Parentheses](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/balanced_parentheses.py)
* [Dijkstras Two Stack Algorithm](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/dijkstras_two_stack_algorithm.py)
* [Evaluate Postfix Notations](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/evaluate_postfix_notations.py)
* [Infix To Postfix Conversion](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/infix_to_postfix_conversion.py)
* [Infix To Prefix Conversion](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/infix_to_prefix_conversion.py)
* [Linked Stack](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/linked_stack.py)
* [Next Greater Element](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/next_greater_element.py)
* [Postfix Evaluation](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/postfix_evaluation.py)
* [Prefix Evaluation](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/prefix_evaluation.py)
* [Stack](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/stack.py)
* [Stack Using Dll](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/stack_using_dll.py)
* [Stock Span Problem](https://github.com/TheAlgorithms/Python/blob/master/data_structures/stacks/stock_span_problem.py)
* Trie
* [Trie](https://github.com/TheAlgorithms/Python/blob/master/data_structures/trie/trie.py)
## Digital Image Processing
* [Change Brightness](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/change_brightness.py)
* [Change Contrast](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/change_contrast.py)
* [Convert To Negative](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/convert_to_negative.py)
* Dithering
* [Burkes](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/dithering/burkes.py)
* Edge Detection
* [Canny](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/edge_detection/canny.py)
* Filters
* [Bilateral Filter](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/bilateral_filter.py)
* [Convolve](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/convolve.py)
* [Gaussian Filter](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/gaussian_filter.py)
* [Median Filter](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/median_filter.py)
* [Sobel Filter](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/filters/sobel_filter.py)
* Histogram Equalization
* [Histogram Stretch](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/histogram_equalization/histogram_stretch.py)
* [Index Calculation](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/index_calculation.py)
* Resize
* [Resize](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/resize/resize.py)
* Rotation
* [Rotation](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/rotation/rotation.py)
* [Sepia](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/sepia.py)
* [Test Digital Image Processing](https://github.com/TheAlgorithms/Python/blob/master/digital_image_processing/test_digital_image_processing.py)
## Divide And Conquer
* [Closest Pair Of Points](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/closest_pair_of_points.py)
* [Convex Hull](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/convex_hull.py)
* [Heaps Algorithm](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/heaps_algorithm.py)
* [Heaps Algorithm Iterative](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/heaps_algorithm_iterative.py)
* [Inversions](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/inversions.py)
* [Kth Order Statistic](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/kth_order_statistic.py)
* [Max Difference Pair](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/max_difference_pair.py)
* [Max Subarray Sum](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/max_subarray_sum.py)
* [Mergesort](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/mergesort.py)
* [Peak](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/peak.py)
* [Power](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/power.py)
* [Strassen Matrix Multiplication](https://github.com/TheAlgorithms/Python/blob/master/divide_and_conquer/strassen_matrix_multiplication.py)
## Dynamic Programming
* [Abbreviation](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/abbreviation.py)
* [Bitmask](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/bitmask.py)
* [Catalan Numbers](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/catalan_numbers.py)
* [Climbing Stairs](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/climbing_stairs.py)
* [Edit Distance](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/edit_distance.py)
* [Factorial](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/factorial.py)
* [Fast Fibonacci](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/fast_fibonacci.py)
* [Fibonacci](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/fibonacci.py)
* [Floyd Warshall](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/floyd_warshall.py)
* [Fractional Knapsack](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/fractional_knapsack.py)
* [Fractional Knapsack 2](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/fractional_knapsack_2.py)
* [Integer Partition](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/integer_partition.py)
* [Iterating Through Submasks](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/iterating_through_submasks.py)
* [Knapsack](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/knapsack.py)
* [Longest Common Subsequence](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/longest_common_subsequence.py)
* [Longest Increasing Subsequence](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/longest_increasing_subsequence.py)
* [Longest Increasing Subsequence O(Nlogn)](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/longest_increasing_subsequence_o(nlogn).py)
* [Longest Sub Array](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/longest_sub_array.py)
* [Matrix Chain Order](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/matrix_chain_order.py)
* [Max Non Adjacent Sum](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/max_non_adjacent_sum.py)
* [Max Sub Array](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/max_sub_array.py)
* [Max Sum Contiguous Subsequence](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/max_sum_contiguous_subsequence.py)
* [Minimum Coin Change](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/minimum_coin_change.py)
* [Minimum Cost Path](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/minimum_cost_path.py)
* [Minimum Partition](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/minimum_partition.py)
* [Minimum Steps To One](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/minimum_steps_to_one.py)
* [Optimal Binary Search Tree](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/optimal_binary_search_tree.py)
* [Rod Cutting](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/rod_cutting.py)
* [Subset Generation](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/subset_generation.py)
* [Sum Of Subset](https://github.com/TheAlgorithms/Python/blob/master/dynamic_programming/sum_of_subset.py)
## Electronics
* [Electric Power](https://github.com/TheAlgorithms/Python/blob/master/electronics/electric_power.py)
* [Ohms Law](https://github.com/TheAlgorithms/Python/blob/master/electronics/ohms_law.py)
## File Transfer
* [Receive File](https://github.com/TheAlgorithms/Python/blob/master/file_transfer/receive_file.py)
* [Send File](https://github.com/TheAlgorithms/Python/blob/master/file_transfer/send_file.py)
* Tests
* [Test Send File](https://github.com/TheAlgorithms/Python/blob/master/file_transfer/tests/test_send_file.py)
## Fractals
* [Koch Snowflake](https://github.com/TheAlgorithms/Python/blob/master/fractals/koch_snowflake.py)
* [Mandelbrot](https://github.com/TheAlgorithms/Python/blob/master/fractals/mandelbrot.py)
* [Sierpinski Triangle](https://github.com/TheAlgorithms/Python/blob/master/fractals/sierpinski_triangle.py)
## Fuzzy Logic
* [Fuzzy Operations](https://github.com/TheAlgorithms/Python/blob/master/fuzzy_logic/fuzzy_operations.py)
## Genetic Algorithm
* [Basic String](https://github.com/TheAlgorithms/Python/blob/master/genetic_algorithm/basic_string.py)
## Geodesy
* [Haversine Distance](https://github.com/TheAlgorithms/Python/blob/master/geodesy/haversine_distance.py)
* [Lamberts Ellipsoidal Distance](https://github.com/TheAlgorithms/Python/blob/master/geodesy/lamberts_ellipsoidal_distance.py)
## Graphics
* [Bezier Curve](https://github.com/TheAlgorithms/Python/blob/master/graphics/bezier_curve.py)
* [Vector3 For 2D Rendering](https://github.com/TheAlgorithms/Python/blob/master/graphics/vector3_for_2d_rendering.py)
## Graphs
* [A Star](https://github.com/TheAlgorithms/Python/blob/master/graphs/a_star.py)
* [Articulation Points](https://github.com/TheAlgorithms/Python/blob/master/graphs/articulation_points.py)
* [Basic Graphs](https://github.com/TheAlgorithms/Python/blob/master/graphs/basic_graphs.py)
* [Bellman Ford](https://github.com/TheAlgorithms/Python/blob/master/graphs/bellman_ford.py)
* [Bfs Shortest Path](https://github.com/TheAlgorithms/Python/blob/master/graphs/bfs_shortest_path.py)
* [Bfs Zero One Shortest Path](https://github.com/TheAlgorithms/Python/blob/master/graphs/bfs_zero_one_shortest_path.py)
* [Bidirectional A Star](https://github.com/TheAlgorithms/Python/blob/master/graphs/bidirectional_a_star.py)
* [Bidirectional Breadth First Search](https://github.com/TheAlgorithms/Python/blob/master/graphs/bidirectional_breadth_first_search.py)
* [Breadth First Search](https://github.com/TheAlgorithms/Python/blob/master/graphs/breadth_first_search.py)
* [Breadth First Search 2](https://github.com/TheAlgorithms/Python/blob/master/graphs/breadth_first_search_2.py)
* [Breadth First Search Shortest Path](https://github.com/TheAlgorithms/Python/blob/master/graphs/breadth_first_search_shortest_path.py)
* [Check Bipartite Graph Bfs](https://github.com/TheAlgorithms/Python/blob/master/graphs/check_bipartite_graph_bfs.py)
* [Check Bipartite Graph Dfs](https://github.com/TheAlgorithms/Python/blob/master/graphs/check_bipartite_graph_dfs.py)
* [Connected Components](https://github.com/TheAlgorithms/Python/blob/master/graphs/connected_components.py)
* [Depth First Search](https://github.com/TheAlgorithms/Python/blob/master/graphs/depth_first_search.py)
* [Depth First Search 2](https://github.com/TheAlgorithms/Python/blob/master/graphs/depth_first_search_2.py)
* [Dijkstra](https://github.com/TheAlgorithms/Python/blob/master/graphs/dijkstra.py)
* [Dijkstra 2](https://github.com/TheAlgorithms/Python/blob/master/graphs/dijkstra_2.py)
* [Dijkstra Algorithm](https://github.com/TheAlgorithms/Python/blob/master/graphs/dijkstra_algorithm.py)
* [Dinic](https://github.com/TheAlgorithms/Python/blob/master/graphs/dinic.py)
* [Directed And Undirected (Weighted) Graph](https://github.com/TheAlgorithms/Python/blob/master/graphs/directed_and_undirected_(weighted)_graph.py)
* [Edmonds Karp Multiple Source And Sink](https://github.com/TheAlgorithms/Python/blob/master/graphs/edmonds_karp_multiple_source_and_sink.py)
* [Eulerian Path And Circuit For Undirected Graph](https://github.com/TheAlgorithms/Python/blob/master/graphs/eulerian_path_and_circuit_for_undirected_graph.py)
* [Even Tree](https://github.com/TheAlgorithms/Python/blob/master/graphs/even_tree.py)
* [Finding Bridges](https://github.com/TheAlgorithms/Python/blob/master/graphs/finding_bridges.py)
* [Frequent Pattern Graph Miner](https://github.com/TheAlgorithms/Python/blob/master/graphs/frequent_pattern_graph_miner.py)
* [G Topological Sort](https://github.com/TheAlgorithms/Python/blob/master/graphs/g_topological_sort.py)
* [Gale Shapley Bigraph](https://github.com/TheAlgorithms/Python/blob/master/graphs/gale_shapley_bigraph.py)
* [Graph List](https://github.com/TheAlgorithms/Python/blob/master/graphs/graph_list.py)
* [Graph Matrix](https://github.com/TheAlgorithms/Python/blob/master/graphs/graph_matrix.py)
* [Graphs Floyd Warshall](https://github.com/TheAlgorithms/Python/blob/master/graphs/graphs_floyd_warshall.py)
* [Greedy Best First](https://github.com/TheAlgorithms/Python/blob/master/graphs/greedy_best_first.py)
* [Kahns Algorithm Long](https://github.com/TheAlgorithms/Python/blob/master/graphs/kahns_algorithm_long.py)
* [Kahns Algorithm Topo](https://github.com/TheAlgorithms/Python/blob/master/graphs/kahns_algorithm_topo.py)
* [Karger](https://github.com/TheAlgorithms/Python/blob/master/graphs/karger.py)
* [Markov Chain](https://github.com/TheAlgorithms/Python/blob/master/graphs/markov_chain.py)
* [Minimum Spanning Tree Boruvka](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_boruvka.py)
* [Minimum Spanning Tree Kruskal](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_kruskal.py)
* [Minimum Spanning Tree Kruskal2](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_kruskal2.py)
* [Minimum Spanning Tree Prims](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_prims.py)
* [Minimum Spanning Tree Prims2](https://github.com/TheAlgorithms/Python/blob/master/graphs/minimum_spanning_tree_prims2.py)
* [Multi Heuristic Astar](https://github.com/TheAlgorithms/Python/blob/master/graphs/multi_heuristic_astar.py)
* [Page Rank](https://github.com/TheAlgorithms/Python/blob/master/graphs/page_rank.py)
* [Prim](https://github.com/TheAlgorithms/Python/blob/master/graphs/prim.py)
* [Scc Kosaraju](https://github.com/TheAlgorithms/Python/blob/master/graphs/scc_kosaraju.py)
* [Strongly Connected Components](https://github.com/TheAlgorithms/Python/blob/master/graphs/strongly_connected_components.py)
* [Tarjans Scc](https://github.com/TheAlgorithms/Python/blob/master/graphs/tarjans_scc.py)
* Tests
* [Test Min Spanning Tree Kruskal](https://github.com/TheAlgorithms/Python/blob/master/graphs/tests/test_min_spanning_tree_kruskal.py)
* [Test Min Spanning Tree Prim](https://github.com/TheAlgorithms/Python/blob/master/graphs/tests/test_min_spanning_tree_prim.py)
## Hashes
* [Adler32](https://github.com/TheAlgorithms/Python/blob/master/hashes/adler32.py)
* [Chaos Machine](https://github.com/TheAlgorithms/Python/blob/master/hashes/chaos_machine.py)
* [Djb2](https://github.com/TheAlgorithms/Python/blob/master/hashes/djb2.py)
* [Enigma Machine](https://github.com/TheAlgorithms/Python/blob/master/hashes/enigma_machine.py)
* [Hamming Code](https://github.com/TheAlgorithms/Python/blob/master/hashes/hamming_code.py)
* [Md5](https://github.com/TheAlgorithms/Python/blob/master/hashes/md5.py)
* [Sdbm](https://github.com/TheAlgorithms/Python/blob/master/hashes/sdbm.py)
* [Sha1](https://github.com/TheAlgorithms/Python/blob/master/hashes/sha1.py)
## Knapsack
* [Greedy Knapsack](https://github.com/TheAlgorithms/Python/blob/master/knapsack/greedy_knapsack.py)
* [Knapsack](https://github.com/TheAlgorithms/Python/blob/master/knapsack/knapsack.py)
* Tests
* [Test Greedy Knapsack](https://github.com/TheAlgorithms/Python/blob/master/knapsack/tests/test_greedy_knapsack.py)
* [Test Knapsack](https://github.com/TheAlgorithms/Python/blob/master/knapsack/tests/test_knapsack.py)
## Linear Algebra
* Src
* [Conjugate Gradient](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/conjugate_gradient.py)
* [Lib](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/lib.py)
* [Polynom For Points](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/polynom_for_points.py)
* [Power Iteration](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/power_iteration.py)
* [Rayleigh Quotient](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/rayleigh_quotient.py)
* [Test Linear Algebra](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/test_linear_algebra.py)
* [Transformations 2D](https://github.com/TheAlgorithms/Python/blob/master/linear_algebra/src/transformations_2d.py)
## Machine Learning
* [Astar](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/astar.py)
* [Data Transformations](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/data_transformations.py)
* [Decision Tree](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/decision_tree.py)
* Forecasting
* [Run](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/forecasting/run.py)
* [Gaussian Naive Bayes](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gaussian_naive_bayes.py)
* [Gradient Boosting Regressor](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_boosting_regressor.py)
* [Gradient Descent](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/gradient_descent.py)
* [K Means Clust](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_means_clust.py)
* [K Nearest Neighbours](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/k_nearest_neighbours.py)
* [Knn Sklearn](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/knn_sklearn.py)
* [Linear Discriminant Analysis](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/linear_discriminant_analysis.py)
* [Linear Regression](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/linear_regression.py)
* [Logistic Regression](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/logistic_regression.py)
* Lstm
* [Lstm Prediction](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/lstm/lstm_prediction.py)
* [Multilayer Perceptron Classifier](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/multilayer_perceptron_classifier.py)
* [Polymonial Regression](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/polymonial_regression.py)
* [Random Forest Classifier](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/random_forest_classifier.py)
* [Random Forest Regressor](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/random_forest_regressor.py)
* [Scoring Functions](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/scoring_functions.py)
* [Sequential Minimum Optimization](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/sequential_minimum_optimization.py)
* [Similarity Search](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/similarity_search.py)
* [Support Vector Machines](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/support_vector_machines.py)
* [Word Frequency Functions](https://github.com/TheAlgorithms/Python/blob/master/machine_learning/word_frequency_functions.py)
## Maths
* [3N Plus 1](https://github.com/TheAlgorithms/Python/blob/master/maths/3n_plus_1.py)
* [Abs](https://github.com/TheAlgorithms/Python/blob/master/maths/abs.py)
* [Abs Max](https://github.com/TheAlgorithms/Python/blob/master/maths/abs_max.py)
* [Abs Min](https://github.com/TheAlgorithms/Python/blob/master/maths/abs_min.py)
* [Add](https://github.com/TheAlgorithms/Python/blob/master/maths/add.py)
* [Aliquot Sum](https://github.com/TheAlgorithms/Python/blob/master/maths/aliquot_sum.py)
* [Allocation Number](https://github.com/TheAlgorithms/Python/blob/master/maths/allocation_number.py)
* [Area](https://github.com/TheAlgorithms/Python/blob/master/maths/area.py)
* [Area Under Curve](https://github.com/TheAlgorithms/Python/blob/master/maths/area_under_curve.py)
* [Armstrong Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/armstrong_numbers.py)
* [Average Mean](https://github.com/TheAlgorithms/Python/blob/master/maths/average_mean.py)
* [Average Median](https://github.com/TheAlgorithms/Python/blob/master/maths/average_median.py)
* [Average Mode](https://github.com/TheAlgorithms/Python/blob/master/maths/average_mode.py)
* [Bailey Borwein Plouffe](https://github.com/TheAlgorithms/Python/blob/master/maths/bailey_borwein_plouffe.py)
* [Basic Maths](https://github.com/TheAlgorithms/Python/blob/master/maths/basic_maths.py)
* [Binary Exp Mod](https://github.com/TheAlgorithms/Python/blob/master/maths/binary_exp_mod.py)
* [Binary Exponentiation](https://github.com/TheAlgorithms/Python/blob/master/maths/binary_exponentiation.py)
* [Binary Exponentiation 2](https://github.com/TheAlgorithms/Python/blob/master/maths/binary_exponentiation_2.py)
* [Binary Exponentiation 3](https://github.com/TheAlgorithms/Python/blob/master/maths/binary_exponentiation_3.py)
* [Binomial Coefficient](https://github.com/TheAlgorithms/Python/blob/master/maths/binomial_coefficient.py)
* [Binomial Distribution](https://github.com/TheAlgorithms/Python/blob/master/maths/binomial_distribution.py)
* [Bisection](https://github.com/TheAlgorithms/Python/blob/master/maths/bisection.py)
* [Ceil](https://github.com/TheAlgorithms/Python/blob/master/maths/ceil.py)
* [Chudnovsky Algorithm](https://github.com/TheAlgorithms/Python/blob/master/maths/chudnovsky_algorithm.py)
* [Collatz Sequence](https://github.com/TheAlgorithms/Python/blob/master/maths/collatz_sequence.py)
* [Combinations](https://github.com/TheAlgorithms/Python/blob/master/maths/combinations.py)
* [Decimal Isolate](https://github.com/TheAlgorithms/Python/blob/master/maths/decimal_isolate.py)
* [Entropy](https://github.com/TheAlgorithms/Python/blob/master/maths/entropy.py)
* [Euclidean Distance](https://github.com/TheAlgorithms/Python/blob/master/maths/euclidean_distance.py)
* [Euclidean Gcd](https://github.com/TheAlgorithms/Python/blob/master/maths/euclidean_gcd.py)
* [Euler Method](https://github.com/TheAlgorithms/Python/blob/master/maths/euler_method.py)
* [Eulers Totient](https://github.com/TheAlgorithms/Python/blob/master/maths/eulers_totient.py)
* [Extended Euclidean Algorithm](https://github.com/TheAlgorithms/Python/blob/master/maths/extended_euclidean_algorithm.py)
* [Factorial Iterative](https://github.com/TheAlgorithms/Python/blob/master/maths/factorial_iterative.py)
* [Factorial Python](https://github.com/TheAlgorithms/Python/blob/master/maths/factorial_python.py)
* [Factorial Recursive](https://github.com/TheAlgorithms/Python/blob/master/maths/factorial_recursive.py)
* [Factors](https://github.com/TheAlgorithms/Python/blob/master/maths/factors.py)
* [Fermat Little Theorem](https://github.com/TheAlgorithms/Python/blob/master/maths/fermat_little_theorem.py)
* [Fibonacci](https://github.com/TheAlgorithms/Python/blob/master/maths/fibonacci.py)
* [Fibonacci Sequence Recursion](https://github.com/TheAlgorithms/Python/blob/master/maths/fibonacci_sequence_recursion.py)
* [Find Max](https://github.com/TheAlgorithms/Python/blob/master/maths/find_max.py)
* [Find Max Recursion](https://github.com/TheAlgorithms/Python/blob/master/maths/find_max_recursion.py)
* [Find Min](https://github.com/TheAlgorithms/Python/blob/master/maths/find_min.py)
* [Find Min Recursion](https://github.com/TheAlgorithms/Python/blob/master/maths/find_min_recursion.py)
* [Floor](https://github.com/TheAlgorithms/Python/blob/master/maths/floor.py)
* [Gamma](https://github.com/TheAlgorithms/Python/blob/master/maths/gamma.py)
* [Gaussian](https://github.com/TheAlgorithms/Python/blob/master/maths/gaussian.py)
* [Greatest Common Divisor](https://github.com/TheAlgorithms/Python/blob/master/maths/greatest_common_divisor.py)
* [Greedy Coin Change](https://github.com/TheAlgorithms/Python/blob/master/maths/greedy_coin_change.py)
* [Hardy Ramanujanalgo](https://github.com/TheAlgorithms/Python/blob/master/maths/hardy_ramanujanalgo.py)
* [Integration By Simpson Approx](https://github.com/TheAlgorithms/Python/blob/master/maths/integration_by_simpson_approx.py)
* [Is Square Free](https://github.com/TheAlgorithms/Python/blob/master/maths/is_square_free.py)
* [Jaccard Similarity](https://github.com/TheAlgorithms/Python/blob/master/maths/jaccard_similarity.py)
* [Kadanes](https://github.com/TheAlgorithms/Python/blob/master/maths/kadanes.py)
* [Karatsuba](https://github.com/TheAlgorithms/Python/blob/master/maths/karatsuba.py)
* [Krishnamurthy Number](https://github.com/TheAlgorithms/Python/blob/master/maths/krishnamurthy_number.py)
* [Kth Lexicographic Permutation](https://github.com/TheAlgorithms/Python/blob/master/maths/kth_lexicographic_permutation.py)
* [Largest Of Very Large Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/largest_of_very_large_numbers.py)
* [Largest Subarray Sum](https://github.com/TheAlgorithms/Python/blob/master/maths/largest_subarray_sum.py)
* [Least Common Multiple](https://github.com/TheAlgorithms/Python/blob/master/maths/least_common_multiple.py)
* [Line Length](https://github.com/TheAlgorithms/Python/blob/master/maths/line_length.py)
* [Lucas Lehmer Primality Test](https://github.com/TheAlgorithms/Python/blob/master/maths/lucas_lehmer_primality_test.py)
* [Lucas Series](https://github.com/TheAlgorithms/Python/blob/master/maths/lucas_series.py)
* [Matrix Exponentiation](https://github.com/TheAlgorithms/Python/blob/master/maths/matrix_exponentiation.py)
* [Max Sum Sliding Window](https://github.com/TheAlgorithms/Python/blob/master/maths/max_sum_sliding_window.py)
* [Median Of Two Arrays](https://github.com/TheAlgorithms/Python/blob/master/maths/median_of_two_arrays.py)
* [Miller Rabin](https://github.com/TheAlgorithms/Python/blob/master/maths/miller_rabin.py)
* [Mobius Function](https://github.com/TheAlgorithms/Python/blob/master/maths/mobius_function.py)
* [Modular Exponential](https://github.com/TheAlgorithms/Python/blob/master/maths/modular_exponential.py)
* [Monte Carlo](https://github.com/TheAlgorithms/Python/blob/master/maths/monte_carlo.py)
* [Monte Carlo Dice](https://github.com/TheAlgorithms/Python/blob/master/maths/monte_carlo_dice.py)
* [Newton Raphson](https://github.com/TheAlgorithms/Python/blob/master/maths/newton_raphson.py)
* [Number Of Digits](https://github.com/TheAlgorithms/Python/blob/master/maths/number_of_digits.py)
* [Numerical Integration](https://github.com/TheAlgorithms/Python/blob/master/maths/numerical_integration.py)
* [Perfect Cube](https://github.com/TheAlgorithms/Python/blob/master/maths/perfect_cube.py)
* [Perfect Number](https://github.com/TheAlgorithms/Python/blob/master/maths/perfect_number.py)
* [Perfect Square](https://github.com/TheAlgorithms/Python/blob/master/maths/perfect_square.py)
* [Pi Monte Carlo Estimation](https://github.com/TheAlgorithms/Python/blob/master/maths/pi_monte_carlo_estimation.py)
* [Polynomial Evaluation](https://github.com/TheAlgorithms/Python/blob/master/maths/polynomial_evaluation.py)
* [Power Using Recursion](https://github.com/TheAlgorithms/Python/blob/master/maths/power_using_recursion.py)
* [Prime Check](https://github.com/TheAlgorithms/Python/blob/master/maths/prime_check.py)
* [Prime Factors](https://github.com/TheAlgorithms/Python/blob/master/maths/prime_factors.py)
* [Prime Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/prime_numbers.py)
* [Prime Sieve Eratosthenes](https://github.com/TheAlgorithms/Python/blob/master/maths/prime_sieve_eratosthenes.py)
* [Primelib](https://github.com/TheAlgorithms/Python/blob/master/maths/primelib.py)
* [Pythagoras](https://github.com/TheAlgorithms/Python/blob/master/maths/pythagoras.py)
* [Qr Decomposition](https://github.com/TheAlgorithms/Python/blob/master/maths/qr_decomposition.py)
* [Quadratic Equations Complex Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/quadratic_equations_complex_numbers.py)
* [Radians](https://github.com/TheAlgorithms/Python/blob/master/maths/radians.py)
* [Radix2 Fft](https://github.com/TheAlgorithms/Python/blob/master/maths/radix2_fft.py)
* [Relu](https://github.com/TheAlgorithms/Python/blob/master/maths/relu.py)
* [Runge Kutta](https://github.com/TheAlgorithms/Python/blob/master/maths/runge_kutta.py)
* [Segmented Sieve](https://github.com/TheAlgorithms/Python/blob/master/maths/segmented_sieve.py)
* Series
* [Arithmetic Mean](https://github.com/TheAlgorithms/Python/blob/master/maths/series/arithmetic_mean.py)
* [Geometric Mean](https://github.com/TheAlgorithms/Python/blob/master/maths/series/geometric_mean.py)
* [Geometric Series](https://github.com/TheAlgorithms/Python/blob/master/maths/series/geometric_series.py)
* [Harmonic Series](https://github.com/TheAlgorithms/Python/blob/master/maths/series/harmonic_series.py)
* [P Series](https://github.com/TheAlgorithms/Python/blob/master/maths/series/p_series.py)
* [Sieve Of Eratosthenes](https://github.com/TheAlgorithms/Python/blob/master/maths/sieve_of_eratosthenes.py)
* [Sigmoid](https://github.com/TheAlgorithms/Python/blob/master/maths/sigmoid.py)
* [Simpson Rule](https://github.com/TheAlgorithms/Python/blob/master/maths/simpson_rule.py)
* [Softmax](https://github.com/TheAlgorithms/Python/blob/master/maths/softmax.py)
* [Square Root](https://github.com/TheAlgorithms/Python/blob/master/maths/square_root.py)
* [Sum Of Arithmetic Series](https://github.com/TheAlgorithms/Python/blob/master/maths/sum_of_arithmetic_series.py)
* [Sum Of Digits](https://github.com/TheAlgorithms/Python/blob/master/maths/sum_of_digits.py)
* [Sum Of Geometric Progression](https://github.com/TheAlgorithms/Python/blob/master/maths/sum_of_geometric_progression.py)
* [Test Prime Check](https://github.com/TheAlgorithms/Python/blob/master/maths/test_prime_check.py)
* [Trapezoidal Rule](https://github.com/TheAlgorithms/Python/blob/master/maths/trapezoidal_rule.py)
* [Triplet Sum](https://github.com/TheAlgorithms/Python/blob/master/maths/triplet_sum.py)
* [Two Pointer](https://github.com/TheAlgorithms/Python/blob/master/maths/two_pointer.py)
* [Two Sum](https://github.com/TheAlgorithms/Python/blob/master/maths/two_sum.py)
* [Ugly Numbers](https://github.com/TheAlgorithms/Python/blob/master/maths/ugly_numbers.py)
* [Volume](https://github.com/TheAlgorithms/Python/blob/master/maths/volume.py)
* [Zellers Congruence](https://github.com/TheAlgorithms/Python/blob/master/maths/zellers_congruence.py)
## Matrix
* [Count Islands In Matrix](https://github.com/TheAlgorithms/Python/blob/master/matrix/count_islands_in_matrix.py)
* [Inverse Of Matrix](https://github.com/TheAlgorithms/Python/blob/master/matrix/inverse_of_matrix.py)
* [Matrix Class](https://github.com/TheAlgorithms/Python/blob/master/matrix/matrix_class.py)
* [Matrix Operation](https://github.com/TheAlgorithms/Python/blob/master/matrix/matrix_operation.py)
* [Nth Fibonacci Using Matrix Exponentiation](https://github.com/TheAlgorithms/Python/blob/master/matrix/nth_fibonacci_using_matrix_exponentiation.py)
* [Rotate Matrix](https://github.com/TheAlgorithms/Python/blob/master/matrix/rotate_matrix.py)
* [Searching In Sorted Matrix](https://github.com/TheAlgorithms/Python/blob/master/matrix/searching_in_sorted_matrix.py)
* [Sherman Morrison](https://github.com/TheAlgorithms/Python/blob/master/matrix/sherman_morrison.py)
* [Spiral Print](https://github.com/TheAlgorithms/Python/blob/master/matrix/spiral_print.py)
* Tests
* [Test Matrix Operation](https://github.com/TheAlgorithms/Python/blob/master/matrix/tests/test_matrix_operation.py)
## Networking Flow
* [Ford Fulkerson](https://github.com/TheAlgorithms/Python/blob/master/networking_flow/ford_fulkerson.py)
* [Minimum Cut](https://github.com/TheAlgorithms/Python/blob/master/networking_flow/minimum_cut.py)
## Neural Network
* [2 Hidden Layers Neural Network](https://github.com/TheAlgorithms/Python/blob/master/neural_network/2_hidden_layers_neural_network.py)
* [Back Propagation Neural Network](https://github.com/TheAlgorithms/Python/blob/master/neural_network/back_propagation_neural_network.py)
* [Convolution Neural Network](https://github.com/TheAlgorithms/Python/blob/master/neural_network/convolution_neural_network.py)
* [Perceptron](https://github.com/TheAlgorithms/Python/blob/master/neural_network/perceptron.py)
## Other
* [Activity Selection](https://github.com/TheAlgorithms/Python/blob/master/other/activity_selection.py)
* [Davis–Putnam–Logemann–Loveland](https://github.com/TheAlgorithms/Python/blob/master/other/davis–putnam–logemann–loveland.py)
* [Dijkstra Bankers Algorithm](https://github.com/TheAlgorithms/Python/blob/master/other/dijkstra_bankers_algorithm.py)
* [Doomsday](https://github.com/TheAlgorithms/Python/blob/master/other/doomsday.py)
* [Fischer Yates Shuffle](https://github.com/TheAlgorithms/Python/blob/master/other/fischer_yates_shuffle.py)
* [Gauss Easter](https://github.com/TheAlgorithms/Python/blob/master/other/gauss_easter.py)
* [Graham Scan](https://github.com/TheAlgorithms/Python/blob/master/other/graham_scan.py)
* [Greedy](https://github.com/TheAlgorithms/Python/blob/master/other/greedy.py)
* [Least Recently Used](https://github.com/TheAlgorithms/Python/blob/master/other/least_recently_used.py)
* [Lfu Cache](https://github.com/TheAlgorithms/Python/blob/master/other/lfu_cache.py)
* [Linear Congruential Generator](https://github.com/TheAlgorithms/Python/blob/master/other/linear_congruential_generator.py)
* [Lru Cache](https://github.com/TheAlgorithms/Python/blob/master/other/lru_cache.py)
* [Magicdiamondpattern](https://github.com/TheAlgorithms/Python/blob/master/other/magicdiamondpattern.py)
* [Nested Brackets](https://github.com/TheAlgorithms/Python/blob/master/other/nested_brackets.py)
* [Password Generator](https://github.com/TheAlgorithms/Python/blob/master/other/password_generator.py)
* [Scoring Algorithm](https://github.com/TheAlgorithms/Python/blob/master/other/scoring_algorithm.py)
* [Sdes](https://github.com/TheAlgorithms/Python/blob/master/other/sdes.py)
* [Tower Of Hanoi](https://github.com/TheAlgorithms/Python/blob/master/other/tower_of_hanoi.py)
## Physics
* [N Body Simulation](https://github.com/TheAlgorithms/Python/blob/master/physics/n_body_simulation.py)
## Project Euler
* Problem 001
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol3.py)
* [Sol4](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol4.py)
* [Sol5](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol5.py)
* [Sol6](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol6.py)
* [Sol7](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_001/sol7.py)
* Problem 002
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol3.py)
* [Sol4](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol4.py)
* [Sol5](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_002/sol5.py)
* Problem 003
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_003/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_003/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_003/sol3.py)
* Problem 004
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_004/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_004/sol2.py)
* Problem 005
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_005/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_005/sol2.py)
* Problem 006
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_006/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_006/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_006/sol3.py)
* [Sol4](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_006/sol4.py)
* Problem 007
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_007/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_007/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_007/sol3.py)
* Problem 008
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_008/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_008/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_008/sol3.py)
* Problem 009
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_009/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_009/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_009/sol3.py)
* Problem 010
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_010/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_010/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_010/sol3.py)
* Problem 011
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_011/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_011/sol2.py)
* Problem 012
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_012/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_012/sol2.py)
* Problem 013
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_013/sol1.py)
* Problem 014
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_014/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_014/sol2.py)
* Problem 015
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_015/sol1.py)
* Problem 016
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_016/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_016/sol2.py)
* Problem 017
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_017/sol1.py)
* Problem 018
* [Solution](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_018/solution.py)
* Problem 019
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_019/sol1.py)
* Problem 020
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_020/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_020/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_020/sol3.py)
* [Sol4](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_020/sol4.py)
* Problem 021
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_021/sol1.py)
* Problem 022
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_022/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_022/sol2.py)
* Problem 023
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_023/sol1.py)
* Problem 024
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_024/sol1.py)
* Problem 025
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_025/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_025/sol2.py)
* [Sol3](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_025/sol3.py)
* Problem 026
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_026/sol1.py)
* Problem 027
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_027/sol1.py)
* Problem 028
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_028/sol1.py)
* Problem 029
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_029/sol1.py)
* Problem 030
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_030/sol1.py)
* Problem 031
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_031/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_031/sol2.py)
* Problem 032
* [Sol32](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_032/sol32.py)
* Problem 033
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_033/sol1.py)
* Problem 034
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_034/sol1.py)
* Problem 035
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_035/sol1.py)
* Problem 036
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_036/sol1.py)
* Problem 037
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_037/sol1.py)
* Problem 038
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_038/sol1.py)
* Problem 039
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_039/sol1.py)
* Problem 040
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_040/sol1.py)
* Problem 041
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_041/sol1.py)
* Problem 042
* [Solution42](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_042/solution42.py)
* Problem 043
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_043/sol1.py)
* Problem 044
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_044/sol1.py)
* Problem 045
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_045/sol1.py)
* Problem 046
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_046/sol1.py)
* Problem 047
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_047/sol1.py)
* Problem 048
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_048/sol1.py)
* Problem 049
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_049/sol1.py)
* Problem 050
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_050/sol1.py)
* Problem 051
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_051/sol1.py)
* Problem 052
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_052/sol1.py)
* Problem 053
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_053/sol1.py)
* Problem 054
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_054/sol1.py)
* [Test Poker Hand](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_054/test_poker_hand.py)
* Problem 055
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_055/sol1.py)
* Problem 056
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_056/sol1.py)
* Problem 057
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_057/sol1.py)
* Problem 058
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_058/sol1.py)
* Problem 059
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_059/sol1.py)
* Problem 062
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_062/sol1.py)
* Problem 063
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_063/sol1.py)
* Problem 064
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_064/sol1.py)
* Problem 065
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_065/sol1.py)
* Problem 067
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_067/sol1.py)
* Problem 069
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_069/sol1.py)
* Problem 070
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_070/sol1.py)
* Problem 071
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_071/sol1.py)
* Problem 072
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_072/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_072/sol2.py)
* Problem 074
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_074/sol1.py)
* [Sol2](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_074/sol2.py)
* Problem 075
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_075/sol1.py)
* Problem 076
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_076/sol1.py)
* Problem 077
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_077/sol1.py)
* Problem 080
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_080/sol1.py)
* Problem 081
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_081/sol1.py)
* Problem 085
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_085/sol1.py)
* Problem 086
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_086/sol1.py)
* Problem 087
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_087/sol1.py)
* Problem 089
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_089/sol1.py)
* Problem 091
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_091/sol1.py)
* Problem 097
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_097/sol1.py)
* Problem 099
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_099/sol1.py)
* Problem 101
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_101/sol1.py)
* Problem 102
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_102/sol1.py)
* Problem 107
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_107/sol1.py)
* Problem 109
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_109/sol1.py)
* Problem 112
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_112/sol1.py)
* Problem 113
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_113/sol1.py)
* Problem 119
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_119/sol1.py)
* Problem 120
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_120/sol1.py)
* Problem 121
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_121/sol1.py)
* Problem 123
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_123/sol1.py)
* Problem 125
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_125/sol1.py)
* Problem 129
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_129/sol1.py)
* Problem 135
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_135/sol1.py)
* Problem 173
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_173/sol1.py)
* Problem 174
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_174/sol1.py)
* Problem 180
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_180/sol1.py)
* Problem 188
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_188/sol1.py)
* Problem 191
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_191/sol1.py)
* Problem 203
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_203/sol1.py)
* Problem 206
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_206/sol1.py)
* Problem 207
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_207/sol1.py)
* Problem 234
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_234/sol1.py)
* Problem 301
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_301/sol1.py)
* Problem 551
* [Sol1](https://github.com/TheAlgorithms/Python/blob/master/project_euler/problem_551/sol1.py)
## Quantum
* [Deutsch Jozsa](https://github.com/TheAlgorithms/Python/blob/master/quantum/deutsch_jozsa.py)
* [Half Adder](https://github.com/TheAlgorithms/Python/blob/master/quantum/half_adder.py)
* [Not Gate](https://github.com/TheAlgorithms/Python/blob/master/quantum/not_gate.py)
* [Quantum Entanglement](https://github.com/TheAlgorithms/Python/blob/master/quantum/quantum_entanglement.py)
* [Ripple Adder Classic](https://github.com/TheAlgorithms/Python/blob/master/quantum/ripple_adder_classic.py)
* [Single Qubit Measure](https://github.com/TheAlgorithms/Python/blob/master/quantum/single_qubit_measure.py)
## Scheduling
* [First Come First Served](https://github.com/TheAlgorithms/Python/blob/master/scheduling/first_come_first_served.py)
* [Round Robin](https://github.com/TheAlgorithms/Python/blob/master/scheduling/round_robin.py)
* [Shortest Job First](https://github.com/TheAlgorithms/Python/blob/master/scheduling/shortest_job_first.py)
## Searches
* [Binary Search](https://github.com/TheAlgorithms/Python/blob/master/searches/binary_search.py)
* [Binary Tree Traversal](https://github.com/TheAlgorithms/Python/blob/master/searches/binary_tree_traversal.py)
* [Double Linear Search](https://github.com/TheAlgorithms/Python/blob/master/searches/double_linear_search.py)
* [Double Linear Search Recursion](https://github.com/TheAlgorithms/Python/blob/master/searches/double_linear_search_recursion.py)
* [Fibonacci Search](https://github.com/TheAlgorithms/Python/blob/master/searches/fibonacci_search.py)
* [Hill Climbing](https://github.com/TheAlgorithms/Python/blob/master/searches/hill_climbing.py)
* [Interpolation Search](https://github.com/TheAlgorithms/Python/blob/master/searches/interpolation_search.py)
* [Jump Search](https://github.com/TheAlgorithms/Python/blob/master/searches/jump_search.py)
* [Linear Search](https://github.com/TheAlgorithms/Python/blob/master/searches/linear_search.py)
* [Quick Select](https://github.com/TheAlgorithms/Python/blob/master/searches/quick_select.py)
* [Sentinel Linear Search](https://github.com/TheAlgorithms/Python/blob/master/searches/sentinel_linear_search.py)
* [Simple Binary Search](https://github.com/TheAlgorithms/Python/blob/master/searches/simple_binary_search.py)
* [Simulated Annealing](https://github.com/TheAlgorithms/Python/blob/master/searches/simulated_annealing.py)
* [Tabu Search](https://github.com/TheAlgorithms/Python/blob/master/searches/tabu_search.py)
* [Ternary Search](https://github.com/TheAlgorithms/Python/blob/master/searches/ternary_search.py)
## Sorts
* [Bead Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bead_sort.py)
* [Bitonic Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bitonic_sort.py)
* [Bogo Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bogo_sort.py)
* [Bubble Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bubble_sort.py)
* [Bucket Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/bucket_sort.py)
* [Cocktail Shaker Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/cocktail_shaker_sort.py)
* [Comb Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/comb_sort.py)
* [Counting Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/counting_sort.py)
* [Cycle Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/cycle_sort.py)
* [Double Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/double_sort.py)
* [External Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/external_sort.py)
* [Gnome Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/gnome_sort.py)
* [Heap Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/heap_sort.py)
* [Insertion Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/insertion_sort.py)
* [Intro Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/intro_sort.py)
* [Iterative Merge Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/iterative_merge_sort.py)
* [Merge Insertion Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/merge_insertion_sort.py)
* [Merge Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/merge_sort.py)
* [Msd Radix Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/msd_radix_sort.py)
* [Natural Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/natural_sort.py)
* [Odd Even Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/odd_even_sort.py)
* [Odd Even Transposition Parallel](https://github.com/TheAlgorithms/Python/blob/master/sorts/odd_even_transposition_parallel.py)
* [Odd Even Transposition Single Threaded](https://github.com/TheAlgorithms/Python/blob/master/sorts/odd_even_transposition_single_threaded.py)
* [Pancake Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/pancake_sort.py)
* [Patience Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/patience_sort.py)
* [Pigeon Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/pigeon_sort.py)
* [Pigeonhole Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/pigeonhole_sort.py)
* [Quick Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/quick_sort.py)
* [Quick Sort 3 Partition](https://github.com/TheAlgorithms/Python/blob/master/sorts/quick_sort_3_partition.py)
* [Radix Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/radix_sort.py)
* [Random Normal Distribution Quicksort](https://github.com/TheAlgorithms/Python/blob/master/sorts/random_normal_distribution_quicksort.py)
* [Random Pivot Quick Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/random_pivot_quick_sort.py)
* [Recursive Bubble Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/recursive_bubble_sort.py)
* [Recursive Insertion Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/recursive_insertion_sort.py)
* [Recursive Mergesort Array](https://github.com/TheAlgorithms/Python/blob/master/sorts/recursive_mergesort_array.py)
* [Recursive Quick Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/recursive_quick_sort.py)
* [Selection Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/selection_sort.py)
* [Shell Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/shell_sort.py)
* [Slowsort](https://github.com/TheAlgorithms/Python/blob/master/sorts/slowsort.py)
* [Stooge Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/stooge_sort.py)
* [Strand Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/strand_sort.py)
* [Tim Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/tim_sort.py)
* [Topological Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/topological_sort.py)
* [Tree Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/tree_sort.py)
* [Unknown Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/unknown_sort.py)
* [Wiggle Sort](https://github.com/TheAlgorithms/Python/blob/master/sorts/wiggle_sort.py)
## Strings
* [Aho Corasick](https://github.com/TheAlgorithms/Python/blob/master/strings/aho_corasick.py)
* [Anagrams](https://github.com/TheAlgorithms/Python/blob/master/strings/anagrams.py)
* [Autocomplete Using Trie](https://github.com/TheAlgorithms/Python/blob/master/strings/autocomplete_using_trie.py)
* [Boyer Moore Search](https://github.com/TheAlgorithms/Python/blob/master/strings/boyer_moore_search.py)
* [Can String Be Rearranged As Palindrome](https://github.com/TheAlgorithms/Python/blob/master/strings/can_string_be_rearranged_as_palindrome.py)
* [Capitalize](https://github.com/TheAlgorithms/Python/blob/master/strings/capitalize.py)
* [Check Anagrams](https://github.com/TheAlgorithms/Python/blob/master/strings/check_anagrams.py)
* [Check Pangram](https://github.com/TheAlgorithms/Python/blob/master/strings/check_pangram.py)
* [Detecting English Programmatically](https://github.com/TheAlgorithms/Python/blob/master/strings/detecting_english_programmatically.py)
* [Frequency Finder](https://github.com/TheAlgorithms/Python/blob/master/strings/frequency_finder.py)
* [Is Palindrome](https://github.com/TheAlgorithms/Python/blob/master/strings/is_palindrome.py)
* [Jaro Winkler](https://github.com/TheAlgorithms/Python/blob/master/strings/jaro_winkler.py)
* [Knuth Morris Pratt](https://github.com/TheAlgorithms/Python/blob/master/strings/knuth_morris_pratt.py)
* [Levenshtein Distance](https://github.com/TheAlgorithms/Python/blob/master/strings/levenshtein_distance.py)
* [Lower](https://github.com/TheAlgorithms/Python/blob/master/strings/lower.py)
* [Manacher](https://github.com/TheAlgorithms/Python/blob/master/strings/manacher.py)
* [Min Cost String Conversion](https://github.com/TheAlgorithms/Python/blob/master/strings/min_cost_string_conversion.py)
* [Naive String Search](https://github.com/TheAlgorithms/Python/blob/master/strings/naive_string_search.py)
* [Palindrome](https://github.com/TheAlgorithms/Python/blob/master/strings/palindrome.py)
* [Prefix Function](https://github.com/TheAlgorithms/Python/blob/master/strings/prefix_function.py)
* [Rabin Karp](https://github.com/TheAlgorithms/Python/blob/master/strings/rabin_karp.py)
* [Remove Duplicate](https://github.com/TheAlgorithms/Python/blob/master/strings/remove_duplicate.py)
* [Reverse Letters](https://github.com/TheAlgorithms/Python/blob/master/strings/reverse_letters.py)
* [Reverse Words](https://github.com/TheAlgorithms/Python/blob/master/strings/reverse_words.py)
* [Split](https://github.com/TheAlgorithms/Python/blob/master/strings/split.py)
* [Swap Case](https://github.com/TheAlgorithms/Python/blob/master/strings/swap_case.py)
* [Upper](https://github.com/TheAlgorithms/Python/blob/master/strings/upper.py)
* [Word Occurrence](https://github.com/TheAlgorithms/Python/blob/master/strings/word_occurrence.py)
* [Word Patterns](https://github.com/TheAlgorithms/Python/blob/master/strings/word_patterns.py)
* [Z Function](https://github.com/TheAlgorithms/Python/blob/master/strings/z_function.py)
## Web Programming
* [Co2 Emission](https://github.com/TheAlgorithms/Python/blob/master/web_programming/co2_emission.py)
* [Covid Stats Via Xpath](https://github.com/TheAlgorithms/Python/blob/master/web_programming/covid_stats_via_xpath.py)
* [Crawl Google Results](https://github.com/TheAlgorithms/Python/blob/master/web_programming/crawl_google_results.py)
* [Crawl Google Scholar Citation](https://github.com/TheAlgorithms/Python/blob/master/web_programming/crawl_google_scholar_citation.py)
* [Currency Converter](https://github.com/TheAlgorithms/Python/blob/master/web_programming/currency_converter.py)
* [Current Stock Price](https://github.com/TheAlgorithms/Python/blob/master/web_programming/current_stock_price.py)
* [Current Weather](https://github.com/TheAlgorithms/Python/blob/master/web_programming/current_weather.py)
* [Daily Horoscope](https://github.com/TheAlgorithms/Python/blob/master/web_programming/daily_horoscope.py)
* [Emails From Url](https://github.com/TheAlgorithms/Python/blob/master/web_programming/emails_from_url.py)
* [Fetch Bbc News](https://github.com/TheAlgorithms/Python/blob/master/web_programming/fetch_bbc_news.py)
* [Fetch Github Info](https://github.com/TheAlgorithms/Python/blob/master/web_programming/fetch_github_info.py)
* [Fetch Jobs](https://github.com/TheAlgorithms/Python/blob/master/web_programming/fetch_jobs.py)
* [Get Imdb Top 250 Movies Csv](https://github.com/TheAlgorithms/Python/blob/master/web_programming/get_imdb_top_250_movies_csv.py)
* [Get Imdbtop](https://github.com/TheAlgorithms/Python/blob/master/web_programming/get_imdbtop.py)
* [Instagram Crawler](https://github.com/TheAlgorithms/Python/blob/master/web_programming/instagram_crawler.py)
* [Instagram Pic](https://github.com/TheAlgorithms/Python/blob/master/web_programming/instagram_pic.py)
* [Instagram Video](https://github.com/TheAlgorithms/Python/blob/master/web_programming/instagram_video.py)
* [Recaptcha Verification](https://github.com/TheAlgorithms/Python/blob/master/web_programming/recaptcha_verification.py)
* [Slack Message](https://github.com/TheAlgorithms/Python/blob/master/web_programming/slack_message.py)
* [Test Fetch Github Info](https://github.com/TheAlgorithms/Python/blob/master/web_programming/test_fetch_github_info.py)
* [World Covid19 Stats](https://github.com/TheAlgorithms/Python/blob/master/web_programming/world_covid19_stats.py)
| 1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| #!/usr/bin/env python3
from typing import Optional
def decrypt_caesar_with_chi_squared(
ciphertext: str,
cipher_alphabet: Optional[list[str]] = None,
frequencies_dict: Optional[dict[str, float]] = None,
case_sensetive: bool = False,
) -> tuple[int, float, str]:
"""
Basic Usage
===========
Arguments:
* ciphertext (str): the text to decode (encoded with the caesar cipher)
Optional Arguments:
* cipher_alphabet (list): the alphabet used for the cipher (each letter is
a string separated by commas)
* frequencies_dict (dict): a dictionary of word frequencies where keys are
the letters and values are a percentage representation of the frequency as
a decimal/float
* case_sensetive (bool): a boolean value: True if the case matters during
decryption, False if it doesn't
Returns:
* A tuple in the form of:
(
most_likely_cipher,
most_likely_cipher_chi_squared_value,
decoded_most_likely_cipher
)
where...
- most_likely_cipher is an integer representing the shift of the smallest
chi-squared statistic (most likely key)
- most_likely_cipher_chi_squared_value is a float representing the
chi-squared statistic of the most likely shift
- decoded_most_likely_cipher is a string with the decoded cipher
(decoded by the most_likely_cipher key)
The Chi-squared test
====================
The caesar cipher
-----------------
The caesar cipher is a very insecure encryption algorithm, however it has
been used since Julius Caesar. The cipher is a simple substitution cipher
where each character in the plain text is replaced by a character in the
alphabet a certain number of characters after the original character. The
number of characters away is called the shift or key. For example:
Plain text: hello
Key: 1
Cipher text: ifmmp
(each letter in hello has been shifted one to the right in the eng. alphabet)
As you can imagine, this doesn't provide lots of security. In fact
decrypting ciphertext by brute-force is extremely easy even by hand. However
one way to do that is the chi-squared test.
The chi-squared test
-------------------
Each letter in the english alphabet has a frequency, or the amount of times
it shows up compared to other letters (usually expressed as a decimal
representing the percentage likelihood). The most common letter in the
english language is "e" with a frequency of 0.11162 or 11.162%. The test is
completed in the following fashion.
1. The ciphertext is decoded in a brute force way (every combination of the
26 possible combinations)
2. For every combination, for each letter in the combination, the average
amount of times the letter should appear the message is calculated by
multiplying the total number of characters by the frequency of the letter
For example:
In a message of 100 characters, e should appear around 11.162 times.
3. Then, to calculate the margin of error (the amount of times the letter
SHOULD appear with the amount of times the letter DOES appear), we use
the chi-squared test. The following formula is used:
Let:
- n be the number of times the letter actually appears
- p be the predicted value of the number of times the letter should
appear (see #2)
- let v be the chi-squared test result (referred to here as chi-squared
value/statistic)
(n - p)^2
--------- = v
p
4. Each chi squared value for each letter is then added up to the total.
The total is the chi-squared statistic for that encryption key.
5. The encryption key with the lowest chi-squared value is the most likely
to be the decoded answer.
Further Reading
================
* http://practicalcryptography.com/cryptanalysis/text-characterisation/chi-squared-
statistic/
* https://en.wikipedia.org/wiki/Letter_frequency
* https://en.wikipedia.org/wiki/Chi-squared_test
* https://en.m.wikipedia.org/wiki/Caesar_cipher
Doctests
========
>>> decrypt_caesar_with_chi_squared(
... 'dof pz aol jhlzhy jpwoly zv wvwbshy? pa pz avv lhzf av jyhjr!'
... ) # doctest: +NORMALIZE_WHITESPACE
(7, 3129.228005747531,
'why is the caesar cipher so popular? it is too easy to crack!')
>>> decrypt_caesar_with_chi_squared('crybd cdbsxq')
(10, 233.35343938980898, 'short string')
>>> decrypt_caesar_with_chi_squared(12)
Traceback (most recent call last):
AttributeError: 'int' object has no attribute 'lower'
"""
alphabet_letters = cipher_alphabet or [chr(i) for i in range(97, 123)]
# If the argument is None or the user provided an empty dictionary
if not frequencies_dict:
# Frequencies of letters in the english language (how much they show up)
frequencies = {
"a": 0.08497,
"b": 0.01492,
"c": 0.02202,
"d": 0.04253,
"e": 0.11162,
"f": 0.02228,
"g": 0.02015,
"h": 0.06094,
"i": 0.07546,
"j": 0.00153,
"k": 0.01292,
"l": 0.04025,
"m": 0.02406,
"n": 0.06749,
"o": 0.07507,
"p": 0.01929,
"q": 0.00095,
"r": 0.07587,
"s": 0.06327,
"t": 0.09356,
"u": 0.02758,
"v": 0.00978,
"w": 0.02560,
"x": 0.00150,
"y": 0.01994,
"z": 0.00077,
}
else:
# Custom frequencies dictionary
frequencies = frequencies_dict
if not case_sensetive:
ciphertext = ciphertext.lower()
# Chi squared statistic values
chi_squared_statistic_values: dict[int, tuple[float, str]] = {}
# cycle through all of the shifts
for shift in range(len(alphabet_letters)):
decrypted_with_shift = ""
# decrypt the message with the shift
for letter in ciphertext:
try:
# Try to index the letter in the alphabet
new_key = (alphabet_letters.index(letter) - shift) % len(
alphabet_letters
)
decrypted_with_shift += alphabet_letters[new_key]
except ValueError:
# Append the character if it isn't in the alphabet
decrypted_with_shift += letter
chi_squared_statistic = 0.0
# Loop through each letter in the decoded message with the shift
for letter in decrypted_with_shift:
if case_sensetive:
if letter in frequencies:
# Get the amount of times the letter occurs in the message
occurrences = decrypted_with_shift.count(letter)
# Get the excepcted amount of times the letter should appear based
# on letter frequencies
expected = frequencies[letter] * occurrences
# Complete the chi squared statistic formula
chi_letter_value = ((occurrences - expected) ** 2) / expected
# Add the margin of error to the total chi squared statistic
chi_squared_statistic += chi_letter_value
else:
if letter.lower() in frequencies:
# Get the amount of times the letter occurs in the message
occurrences = decrypted_with_shift.count(letter)
# Get the excepcted amount of times the letter should appear based
# on letter frequencies
expected = frequencies[letter] * occurrences
# Complete the chi squared statistic formula
chi_letter_value = ((occurrences - expected) ** 2) / expected
# Add the margin of error to the total chi squared statistic
chi_squared_statistic += chi_letter_value
# Add the data to the chi_squared_statistic_values dictionary
chi_squared_statistic_values[shift] = (
chi_squared_statistic,
decrypted_with_shift,
)
# Get the most likely cipher by finding the cipher with the smallest chi squared
# statistic
most_likely_cipher: int = min(
chi_squared_statistic_values, key=chi_squared_statistic_values.get
) # type: ignore # First argument to `min` is not optional
# Get all the data from the most likely cipher (key, decoded message)
(
most_likely_cipher_chi_squared_value,
decoded_most_likely_cipher,
) = chi_squared_statistic_values[most_likely_cipher]
# Return the data on the most likely shift
return (
most_likely_cipher,
most_likely_cipher_chi_squared_value,
decoded_most_likely_cipher,
)
| #!/usr/bin/env python3
from typing import Optional
def decrypt_caesar_with_chi_squared(
ciphertext: str,
cipher_alphabet: Optional[list[str]] = None,
frequencies_dict: Optional[dict[str, float]] = None,
case_sensetive: bool = False,
) -> tuple[int, float, str]:
"""
Basic Usage
===========
Arguments:
* ciphertext (str): the text to decode (encoded with the caesar cipher)
Optional Arguments:
* cipher_alphabet (list): the alphabet used for the cipher (each letter is
a string separated by commas)
* frequencies_dict (dict): a dictionary of word frequencies where keys are
the letters and values are a percentage representation of the frequency as
a decimal/float
* case_sensetive (bool): a boolean value: True if the case matters during
decryption, False if it doesn't
Returns:
* A tuple in the form of:
(
most_likely_cipher,
most_likely_cipher_chi_squared_value,
decoded_most_likely_cipher
)
where...
- most_likely_cipher is an integer representing the shift of the smallest
chi-squared statistic (most likely key)
- most_likely_cipher_chi_squared_value is a float representing the
chi-squared statistic of the most likely shift
- decoded_most_likely_cipher is a string with the decoded cipher
(decoded by the most_likely_cipher key)
The Chi-squared test
====================
The caesar cipher
-----------------
The caesar cipher is a very insecure encryption algorithm, however it has
been used since Julius Caesar. The cipher is a simple substitution cipher
where each character in the plain text is replaced by a character in the
alphabet a certain number of characters after the original character. The
number of characters away is called the shift or key. For example:
Plain text: hello
Key: 1
Cipher text: ifmmp
(each letter in hello has been shifted one to the right in the eng. alphabet)
As you can imagine, this doesn't provide lots of security. In fact
decrypting ciphertext by brute-force is extremely easy even by hand. However
one way to do that is the chi-squared test.
The chi-squared test
-------------------
Each letter in the english alphabet has a frequency, or the amount of times
it shows up compared to other letters (usually expressed as a decimal
representing the percentage likelihood). The most common letter in the
english language is "e" with a frequency of 0.11162 or 11.162%. The test is
completed in the following fashion.
1. The ciphertext is decoded in a brute force way (every combination of the
26 possible combinations)
2. For every combination, for each letter in the combination, the average
amount of times the letter should appear the message is calculated by
multiplying the total number of characters by the frequency of the letter
For example:
In a message of 100 characters, e should appear around 11.162 times.
3. Then, to calculate the margin of error (the amount of times the letter
SHOULD appear with the amount of times the letter DOES appear), we use
the chi-squared test. The following formula is used:
Let:
- n be the number of times the letter actually appears
- p be the predicted value of the number of times the letter should
appear (see #2)
- let v be the chi-squared test result (referred to here as chi-squared
value/statistic)
(n - p)^2
--------- = v
p
4. Each chi squared value for each letter is then added up to the total.
The total is the chi-squared statistic for that encryption key.
5. The encryption key with the lowest chi-squared value is the most likely
to be the decoded answer.
Further Reading
================
* http://practicalcryptography.com/cryptanalysis/text-characterisation/chi-squared-
statistic/
* https://en.wikipedia.org/wiki/Letter_frequency
* https://en.wikipedia.org/wiki/Chi-squared_test
* https://en.m.wikipedia.org/wiki/Caesar_cipher
Doctests
========
>>> decrypt_caesar_with_chi_squared(
... 'dof pz aol jhlzhy jpwoly zv wvwbshy? pa pz avv lhzf av jyhjr!'
... ) # doctest: +NORMALIZE_WHITESPACE
(7, 3129.228005747531,
'why is the caesar cipher so popular? it is too easy to crack!')
>>> decrypt_caesar_with_chi_squared('crybd cdbsxq')
(10, 233.35343938980898, 'short string')
>>> decrypt_caesar_with_chi_squared(12)
Traceback (most recent call last):
AttributeError: 'int' object has no attribute 'lower'
"""
alphabet_letters = cipher_alphabet or [chr(i) for i in range(97, 123)]
# If the argument is None or the user provided an empty dictionary
if not frequencies_dict:
# Frequencies of letters in the english language (how much they show up)
frequencies = {
"a": 0.08497,
"b": 0.01492,
"c": 0.02202,
"d": 0.04253,
"e": 0.11162,
"f": 0.02228,
"g": 0.02015,
"h": 0.06094,
"i": 0.07546,
"j": 0.00153,
"k": 0.01292,
"l": 0.04025,
"m": 0.02406,
"n": 0.06749,
"o": 0.07507,
"p": 0.01929,
"q": 0.00095,
"r": 0.07587,
"s": 0.06327,
"t": 0.09356,
"u": 0.02758,
"v": 0.00978,
"w": 0.02560,
"x": 0.00150,
"y": 0.01994,
"z": 0.00077,
}
else:
# Custom frequencies dictionary
frequencies = frequencies_dict
if not case_sensetive:
ciphertext = ciphertext.lower()
# Chi squared statistic values
chi_squared_statistic_values: dict[int, tuple[float, str]] = {}
# cycle through all of the shifts
for shift in range(len(alphabet_letters)):
decrypted_with_shift = ""
# decrypt the message with the shift
for letter in ciphertext:
try:
# Try to index the letter in the alphabet
new_key = (alphabet_letters.index(letter) - shift) % len(
alphabet_letters
)
decrypted_with_shift += alphabet_letters[new_key]
except ValueError:
# Append the character if it isn't in the alphabet
decrypted_with_shift += letter
chi_squared_statistic = 0.0
# Loop through each letter in the decoded message with the shift
for letter in decrypted_with_shift:
if case_sensetive:
if letter in frequencies:
# Get the amount of times the letter occurs in the message
occurrences = decrypted_with_shift.count(letter)
# Get the excepcted amount of times the letter should appear based
# on letter frequencies
expected = frequencies[letter] * occurrences
# Complete the chi squared statistic formula
chi_letter_value = ((occurrences - expected) ** 2) / expected
# Add the margin of error to the total chi squared statistic
chi_squared_statistic += chi_letter_value
else:
if letter.lower() in frequencies:
# Get the amount of times the letter occurs in the message
occurrences = decrypted_with_shift.count(letter)
# Get the excepcted amount of times the letter should appear based
# on letter frequencies
expected = frequencies[letter] * occurrences
# Complete the chi squared statistic formula
chi_letter_value = ((occurrences - expected) ** 2) / expected
# Add the margin of error to the total chi squared statistic
chi_squared_statistic += chi_letter_value
# Add the data to the chi_squared_statistic_values dictionary
chi_squared_statistic_values[shift] = (
chi_squared_statistic,
decrypted_with_shift,
)
# Get the most likely cipher by finding the cipher with the smallest chi squared
# statistic
most_likely_cipher: int = min( # type: ignore
chi_squared_statistic_values, # type: ignore
key=chi_squared_statistic_values.get, # type: ignore
) # type: ignore
# Get all the data from the most likely cipher (key, decoded message)
(
most_likely_cipher_chi_squared_value,
decoded_most_likely_cipher,
) = chi_squared_statistic_values[most_likely_cipher]
# Return the data on the most likely shift
return (
most_likely_cipher,
most_likely_cipher_chi_squared_value,
decoded_most_likely_cipher,
)
| 1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| beautifulsoup4
fake_useragent
keras
lxml
matplotlib
numpy
opencv-python
pandas
pillow
qiskit
requests
scikit-fuzzy
sklearn
statsmodels
sympy
tensorflow
xgboost
| beautifulsoup4
fake_useragent
keras
lxml
matplotlib
numpy
opencv-python
pandas
pillow
qiskit
requests
scikit-fuzzy
sklearn
statsmodels
sympy
tensorflow
types-requests
xgboost
| 1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| #!/usr/bin/env python3
import hashlib
import importlib.util
import json
import os
import pathlib
from types import ModuleType
import pytest
import requests
PROJECT_EULER_DIR_PATH = pathlib.Path.cwd().joinpath("project_euler")
PROJECT_EULER_ANSWERS_PATH = pathlib.Path.cwd().joinpath(
"scripts", "project_euler_answers.json"
)
with open(PROJECT_EULER_ANSWERS_PATH) as file_handle:
PROBLEM_ANSWERS: dict[str, str] = json.load(file_handle)
def convert_path_to_module(file_path: pathlib.Path) -> ModuleType:
"""Converts a file path to a Python module"""
spec = importlib.util.spec_from_file_location(file_path.name, str(file_path))
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module) # type: ignore
return module
def all_solution_file_paths() -> list[pathlib.Path]:
"""Collects all the solution file path in the Project Euler directory"""
solution_file_paths = []
for problem_dir_path in PROJECT_EULER_DIR_PATH.iterdir():
if problem_dir_path.is_file() or problem_dir_path.name.startswith("_"):
continue
for file_path in problem_dir_path.iterdir():
if file_path.suffix != ".py" or file_path.name.startswith(("_", "test")):
continue
solution_file_paths.append(file_path)
return solution_file_paths
def get_files_url() -> str:
"""Return the pull request number which triggered this action."""
with open(os.environ["GITHUB_EVENT_PATH"]) as file:
event = json.load(file)
return event["pull_request"]["url"] + "/files"
def added_solution_file_path() -> list[pathlib.Path]:
"""Collects only the solution file path which got added in the current
pull request.
This will only be triggered if the script is ran from GitHub Actions.
"""
solution_file_paths = []
headers = {
"Accept": "application/vnd.github.v3+json",
"Authorization": "token " + os.environ["GITHUB_TOKEN"],
}
files = requests.get(get_files_url(), headers=headers).json()
for file in files:
filepath = pathlib.Path.cwd().joinpath(file["filename"])
if (
filepath.suffix != ".py"
or filepath.name.startswith(("_", "test"))
or not filepath.name.startswith("sol")
):
continue
solution_file_paths.append(filepath)
return solution_file_paths
def collect_solution_file_paths() -> list[pathlib.Path]:
if os.environ.get("CI") and os.environ.get("GITHUB_EVENT_NAME") == "pull_request":
# Return only if there are any, otherwise default to all solutions
if filepaths := added_solution_file_path():
return filepaths
return all_solution_file_paths()
@pytest.mark.parametrize(
"solution_path",
collect_solution_file_paths(),
ids=lambda path: f"{path.parent.name}/{path.name}",
)
def test_project_euler(solution_path: pathlib.Path) -> None:
"""Testing for all Project Euler solutions"""
# problem_[extract this part] and pad it with zeroes for width 3
problem_number: str = solution_path.parent.name[8:].zfill(3)
expected: str = PROBLEM_ANSWERS[problem_number]
solution_module = convert_path_to_module(solution_path)
answer = str(solution_module.solution()) # type: ignore
answer = hashlib.sha256(answer.encode()).hexdigest()
assert (
answer == expected
), f"Expected solution to {problem_number} to have hash {expected}, got {answer}"
| #!/usr/bin/env python3
import hashlib
import importlib.util
import json
import os
import pathlib
from types import ModuleType
import pytest
import requests
PROJECT_EULER_DIR_PATH = pathlib.Path.cwd().joinpath("project_euler")
PROJECT_EULER_ANSWERS_PATH = pathlib.Path.cwd().joinpath(
"scripts", "project_euler_answers.json"
)
with open(PROJECT_EULER_ANSWERS_PATH) as file_handle:
PROBLEM_ANSWERS: dict[str, str] = json.load(file_handle)
def convert_path_to_module(file_path: pathlib.Path) -> ModuleType:
"""Converts a file path to a Python module"""
spec = importlib.util.spec_from_file_location(file_path.name, str(file_path))
module = importlib.util.module_from_spec(spec) # type: ignore
spec.loader.exec_module(module) # type: ignore
return module
def all_solution_file_paths() -> list[pathlib.Path]:
"""Collects all the solution file path in the Project Euler directory"""
solution_file_paths = []
for problem_dir_path in PROJECT_EULER_DIR_PATH.iterdir():
if problem_dir_path.is_file() or problem_dir_path.name.startswith("_"):
continue
for file_path in problem_dir_path.iterdir():
if file_path.suffix != ".py" or file_path.name.startswith(("_", "test")):
continue
solution_file_paths.append(file_path)
return solution_file_paths
def get_files_url() -> str:
"""Return the pull request number which triggered this action."""
with open(os.environ["GITHUB_EVENT_PATH"]) as file:
event = json.load(file)
return event["pull_request"]["url"] + "/files"
def added_solution_file_path() -> list[pathlib.Path]:
"""Collects only the solution file path which got added in the current
pull request.
This will only be triggered if the script is ran from GitHub Actions.
"""
solution_file_paths = []
headers = {
"Accept": "application/vnd.github.v3+json",
"Authorization": "token " + os.environ["GITHUB_TOKEN"],
}
files = requests.get(get_files_url(), headers=headers).json()
for file in files:
filepath = pathlib.Path.cwd().joinpath(file["filename"])
if (
filepath.suffix != ".py"
or filepath.name.startswith(("_", "test"))
or not filepath.name.startswith("sol")
):
continue
solution_file_paths.append(filepath)
return solution_file_paths
def collect_solution_file_paths() -> list[pathlib.Path]:
if os.environ.get("CI") and os.environ.get("GITHUB_EVENT_NAME") == "pull_request":
# Return only if there are any, otherwise default to all solutions
if filepaths := added_solution_file_path():
return filepaths
return all_solution_file_paths()
@pytest.mark.parametrize(
"solution_path",
collect_solution_file_paths(),
ids=lambda path: f"{path.parent.name}/{path.name}",
)
def test_project_euler(solution_path: pathlib.Path) -> None:
"""Testing for all Project Euler solutions"""
# problem_[extract this part] and pad it with zeroes for width 3
problem_number: str = solution_path.parent.name[8:].zfill(3)
expected: str = PROBLEM_ANSWERS[problem_number]
solution_module = convert_path_to_module(solution_path)
answer = str(solution_module.solution()) # type: ignore
answer = hashlib.sha256(answer.encode()).hexdigest()
assert (
answer == expected
), f"Expected solution to {problem_number} to have hash {expected}, got {answer}"
| 1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
The nested brackets problem is a problem that determines if a sequence of
brackets are properly nested. A sequence of brackets s is considered properly nested
if any of the following conditions are true:
- s is empty
- s has the form (U) or [U] or {U} where U is a properly nested string
- s has the form VW where V and W are properly nested strings
For example, the string "()()[()]" is properly nested but "[(()]" is not.
The function called is_balanced takes as input a string S which is a sequence of
brackets and returns true if S is nested and false otherwise.
"""
def is_balanced(S):
stack = []
open_brackets = set({"(", "[", "{"})
closed_brackets = set({")", "]", "}"})
open_to_closed = dict({"{": "}", "[": "]", "(": ")"})
for i in range(len(S)):
if S[i] in open_brackets:
stack.append(S[i])
elif S[i] in closed_brackets:
if len(stack) == 0 or (
len(stack) > 0 and open_to_closed[stack.pop()] != S[i]
):
return False
return len(stack) == 0
def main():
s = input("Enter sequence of brackets: ")
if is_balanced(s):
print(s, "is balanced")
else:
print(s, "is not balanced")
if __name__ == "__main__":
main()
| """
The nested brackets problem is a problem that determines if a sequence of
brackets are properly nested. A sequence of brackets s is considered properly nested
if any of the following conditions are true:
- s is empty
- s has the form (U) or [U] or {U} where U is a properly nested string
- s has the form VW where V and W are properly nested strings
For example, the string "()()[()]" is properly nested but "[(()]" is not.
The function called is_balanced takes as input a string S which is a sequence of
brackets and returns true if S is nested and false otherwise.
"""
def is_balanced(S):
stack = []
open_brackets = set({"(", "[", "{"})
closed_brackets = set({")", "]", "}"})
open_to_closed = dict({"{": "}", "[": "]", "(": ")"})
for i in range(len(S)):
if S[i] in open_brackets:
stack.append(S[i])
elif S[i] in closed_brackets:
if len(stack) == 0 or (
len(stack) > 0 and open_to_closed[stack.pop()] != S[i]
):
return False
return len(stack) == 0
def main():
s = input("Enter sequence of brackets: ")
if is_balanced(s):
print(s, "is balanced")
else:
print(s, "is not balanced")
if __name__ == "__main__":
main()
| -1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| def hex_to_bin(hex_num: str) -> int:
"""
Convert a hexadecimal value to its binary equivalent
#https://stackoverflow.com/questions/1425493/convert-hex-to-binary
Here, we have used the bitwise right shift operator: >>
Shifts the bits of the number to the right and fills 0 on voids left as a result.
Similar effect as of dividing the number with some power of two.
Example:
a = 10
a >> 1 = 5
>>> hex_to_bin("AC")
10101100
>>> hex_to_bin("9A4")
100110100100
>>> hex_to_bin(" 12f ")
100101111
>>> hex_to_bin("FfFf")
1111111111111111
>>> hex_to_bin("-fFfF")
-1111111111111111
>>> hex_to_bin("F-f")
Traceback (most recent call last):
...
ValueError: Invalid value was passed to the function
>>> hex_to_bin("")
Traceback (most recent call last):
...
ValueError: No value was passed to the function
"""
hex_num = hex_num.strip()
if not hex_num:
raise ValueError("No value was passed to the function")
is_negative = hex_num[0] == "-"
if is_negative:
hex_num = hex_num[1:]
try:
int_num = int(hex_num, 16)
except ValueError:
raise ValueError("Invalid value was passed to the function")
bin_str = ""
while int_num > 0:
bin_str = str(int_num % 2) + bin_str
int_num >>= 1
return int(("-" + bin_str) if is_negative else bin_str)
if __name__ == "__main__":
import doctest
doctest.testmod()
| def hex_to_bin(hex_num: str) -> int:
"""
Convert a hexadecimal value to its binary equivalent
#https://stackoverflow.com/questions/1425493/convert-hex-to-binary
Here, we have used the bitwise right shift operator: >>
Shifts the bits of the number to the right and fills 0 on voids left as a result.
Similar effect as of dividing the number with some power of two.
Example:
a = 10
a >> 1 = 5
>>> hex_to_bin("AC")
10101100
>>> hex_to_bin("9A4")
100110100100
>>> hex_to_bin(" 12f ")
100101111
>>> hex_to_bin("FfFf")
1111111111111111
>>> hex_to_bin("-fFfF")
-1111111111111111
>>> hex_to_bin("F-f")
Traceback (most recent call last):
...
ValueError: Invalid value was passed to the function
>>> hex_to_bin("")
Traceback (most recent call last):
...
ValueError: No value was passed to the function
"""
hex_num = hex_num.strip()
if not hex_num:
raise ValueError("No value was passed to the function")
is_negative = hex_num[0] == "-"
if is_negative:
hex_num = hex_num[1:]
try:
int_num = int(hex_num, 16)
except ValueError:
raise ValueError("Invalid value was passed to the function")
bin_str = ""
while int_num > 0:
bin_str = str(int_num % 2) + bin_str
int_num >>= 1
return int(("-" + bin_str) if is_negative else bin_str)
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
This is a python3 implementation of binary search tree using recursion
To run tests:
python -m unittest binary_search_tree_recursive.py
To run an example:
python binary_search_tree_recursive.py
"""
import unittest
from typing import Iterator, Optional
class Node:
def __init__(self, label: int, parent: Optional["Node"]) -> None:
self.label = label
self.parent = parent
self.left: Optional[Node] = None
self.right: Optional[Node] = None
class BinarySearchTree:
def __init__(self) -> None:
self.root: Optional[Node] = None
def empty(self) -> None:
"""
Empties the tree
>>> t = BinarySearchTree()
>>> assert t.root is None
>>> t.put(8)
>>> assert t.root is not None
"""
self.root = None
def is_empty(self) -> bool:
"""
Checks if the tree is empty
>>> t = BinarySearchTree()
>>> t.is_empty()
True
>>> t.put(8)
>>> t.is_empty()
False
"""
return self.root is None
def put(self, label: int) -> None:
"""
Put a new node in the tree
>>> t = BinarySearchTree()
>>> t.put(8)
>>> assert t.root.parent is None
>>> assert t.root.label == 8
>>> t.put(10)
>>> assert t.root.right.parent == t.root
>>> assert t.root.right.label == 10
>>> t.put(3)
>>> assert t.root.left.parent == t.root
>>> assert t.root.left.label == 3
"""
self.root = self._put(self.root, label)
def _put(
self, node: Optional[Node], label: int, parent: Optional[Node] = None
) -> Node:
if node is None:
node = Node(label, parent)
else:
if label < node.label:
node.left = self._put(node.left, label, node)
elif label > node.label:
node.right = self._put(node.right, label, node)
else:
raise Exception(f"Node with label {label} already exists")
return node
def search(self, label: int) -> Node:
"""
Searches a node in the tree
>>> t = BinarySearchTree()
>>> t.put(8)
>>> t.put(10)
>>> node = t.search(8)
>>> assert node.label == 8
>>> node = t.search(3)
Traceback (most recent call last):
...
Exception: Node with label 3 does not exist
"""
return self._search(self.root, label)
def _search(self, node: Optional[Node], label: int) -> Node:
if node is None:
raise Exception(f"Node with label {label} does not exist")
else:
if label < node.label:
node = self._search(node.left, label)
elif label > node.label:
node = self._search(node.right, label)
return node
def remove(self, label: int) -> None:
"""
Removes a node in the tree
>>> t = BinarySearchTree()
>>> t.put(8)
>>> t.put(10)
>>> t.remove(8)
>>> assert t.root.label == 10
>>> t.remove(3)
Traceback (most recent call last):
...
Exception: Node with label 3 does not exist
"""
node = self.search(label)
if node.right and node.left:
lowest_node = self._get_lowest_node(node.right)
lowest_node.left = node.left
lowest_node.right = node.right
node.left.parent = lowest_node
if node.right:
node.right.parent = lowest_node
self._reassign_nodes(node, lowest_node)
elif not node.right and node.left:
self._reassign_nodes(node, node.left)
elif node.right and not node.left:
self._reassign_nodes(node, node.right)
else:
self._reassign_nodes(node, None)
def _reassign_nodes(self, node: Node, new_children: Optional[Node]) -> None:
if new_children:
new_children.parent = node.parent
if node.parent:
if node.parent.right == node:
node.parent.right = new_children
else:
node.parent.left = new_children
else:
self.root = new_children
def _get_lowest_node(self, node: Node) -> Node:
if node.left:
lowest_node = self._get_lowest_node(node.left)
else:
lowest_node = node
self._reassign_nodes(node, node.right)
return lowest_node
def exists(self, label: int) -> bool:
"""
Checks if a node exists in the tree
>>> t = BinarySearchTree()
>>> t.put(8)
>>> t.put(10)
>>> t.exists(8)
True
>>> t.exists(3)
False
"""
try:
self.search(label)
return True
except Exception:
return False
def get_max_label(self) -> int:
"""
Gets the max label inserted in the tree
>>> t = BinarySearchTree()
>>> t.get_max_label()
Traceback (most recent call last):
...
Exception: Binary search tree is empty
>>> t.put(8)
>>> t.put(10)
>>> t.get_max_label()
10
"""
if self.root is None:
raise Exception("Binary search tree is empty")
node = self.root
while node.right is not None:
node = node.right
return node.label
def get_min_label(self) -> int:
"""
Gets the min label inserted in the tree
>>> t = BinarySearchTree()
>>> t.get_min_label()
Traceback (most recent call last):
...
Exception: Binary search tree is empty
>>> t.put(8)
>>> t.put(10)
>>> t.get_min_label()
8
"""
if self.root is None:
raise Exception("Binary search tree is empty")
node = self.root
while node.left is not None:
node = node.left
return node.label
def inorder_traversal(self) -> Iterator[Node]:
"""
Return the inorder traversal of the tree
>>> t = BinarySearchTree()
>>> [i.label for i in t.inorder_traversal()]
[]
>>> t.put(8)
>>> t.put(10)
>>> t.put(9)
>>> [i.label for i in t.inorder_traversal()]
[8, 9, 10]
"""
return self._inorder_traversal(self.root)
def _inorder_traversal(self, node: Optional[Node]) -> Iterator[Node]:
if node is not None:
yield from self._inorder_traversal(node.left)
yield node
yield from self._inorder_traversal(node.right)
def preorder_traversal(self) -> Iterator[Node]:
"""
Return the preorder traversal of the tree
>>> t = BinarySearchTree()
>>> [i.label for i in t.preorder_traversal()]
[]
>>> t.put(8)
>>> t.put(10)
>>> t.put(9)
>>> [i.label for i in t.preorder_traversal()]
[8, 10, 9]
"""
return self._preorder_traversal(self.root)
def _preorder_traversal(self, node: Optional[Node]) -> Iterator[Node]:
if node is not None:
yield node
yield from self._preorder_traversal(node.left)
yield from self._preorder_traversal(node.right)
class BinarySearchTreeTest(unittest.TestCase):
@staticmethod
def _get_binary_search_tree() -> BinarySearchTree:
r"""
8
/ \
3 10
/ \ \
1 6 14
/ \ /
4 7 13
\
5
"""
t = BinarySearchTree()
t.put(8)
t.put(3)
t.put(6)
t.put(1)
t.put(10)
t.put(14)
t.put(13)
t.put(4)
t.put(7)
t.put(5)
return t
def test_put(self) -> None:
t = BinarySearchTree()
assert t.is_empty()
t.put(8)
r"""
8
"""
assert t.root is not None
assert t.root.parent is None
assert t.root.label == 8
t.put(10)
r"""
8
\
10
"""
assert t.root.right is not None
assert t.root.right.parent == t.root
assert t.root.right.label == 10
t.put(3)
r"""
8
/ \
3 10
"""
assert t.root.left is not None
assert t.root.left.parent == t.root
assert t.root.left.label == 3
t.put(6)
r"""
8
/ \
3 10
\
6
"""
assert t.root.left.right is not None
assert t.root.left.right.parent == t.root.left
assert t.root.left.right.label == 6
t.put(1)
r"""
8
/ \
3 10
/ \
1 6
"""
assert t.root.left.left is not None
assert t.root.left.left.parent == t.root.left
assert t.root.left.left.label == 1
with self.assertRaises(Exception):
t.put(1)
def test_search(self) -> None:
t = self._get_binary_search_tree()
node = t.search(6)
assert node.label == 6
node = t.search(13)
assert node.label == 13
with self.assertRaises(Exception):
t.search(2)
def test_remove(self) -> None:
t = self._get_binary_search_tree()
t.remove(13)
r"""
8
/ \
3 10
/ \ \
1 6 14
/ \
4 7
\
5
"""
assert t.root is not None
assert t.root.right is not None
assert t.root.right.right is not None
assert t.root.right.right.right is None
assert t.root.right.right.left is None
t.remove(7)
r"""
8
/ \
3 10
/ \ \
1 6 14
/
4
\
5
"""
assert t.root.left is not None
assert t.root.left.right is not None
assert t.root.left.right.left is not None
assert t.root.left.right.right is None
assert t.root.left.right.left.label == 4
t.remove(6)
r"""
8
/ \
3 10
/ \ \
1 4 14
\
5
"""
assert t.root.left.left is not None
assert t.root.left.right.right is not None
assert t.root.left.left.label == 1
assert t.root.left.right.label == 4
assert t.root.left.right.right.label == 5
assert t.root.left.right.left is None
assert t.root.left.left.parent == t.root.left
assert t.root.left.right.parent == t.root.left
t.remove(3)
r"""
8
/ \
4 10
/ \ \
1 5 14
"""
assert t.root is not None
assert t.root.left.label == 4
assert t.root.left.right.label == 5
assert t.root.left.left.label == 1
assert t.root.left.parent == t.root
assert t.root.left.left.parent == t.root.left
assert t.root.left.right.parent == t.root.left
t.remove(4)
r"""
8
/ \
5 10
/ \
1 14
"""
assert t.root.left is not None
assert t.root.left.left is not None
assert t.root.left.label == 5
assert t.root.left.right is None
assert t.root.left.left.label == 1
assert t.root.left.parent == t.root
assert t.root.left.left.parent == t.root.left
def test_remove_2(self) -> None:
t = self._get_binary_search_tree()
t.remove(3)
r"""
8
/ \
4 10
/ \ \
1 6 14
/ \ /
5 7 13
"""
assert t.root is not None
assert t.root.left is not None
assert t.root.left.left is not None
assert t.root.left.right is not None
assert t.root.left.right.left is not None
assert t.root.left.right.right is not None
assert t.root.left.label == 4
assert t.root.left.right.label == 6
assert t.root.left.left.label == 1
assert t.root.left.right.right.label == 7
assert t.root.left.right.left.label == 5
assert t.root.left.parent == t.root
assert t.root.left.right.parent == t.root.left
assert t.root.left.left.parent == t.root.left
assert t.root.left.right.left.parent == t.root.left.right
def test_empty(self) -> None:
t = self._get_binary_search_tree()
t.empty()
assert t.root is None
def test_is_empty(self) -> None:
t = self._get_binary_search_tree()
assert not t.is_empty()
t.empty()
assert t.is_empty()
def test_exists(self) -> None:
t = self._get_binary_search_tree()
assert t.exists(6)
assert not t.exists(-1)
def test_get_max_label(self) -> None:
t = self._get_binary_search_tree()
assert t.get_max_label() == 14
t.empty()
with self.assertRaises(Exception):
t.get_max_label()
def test_get_min_label(self) -> None:
t = self._get_binary_search_tree()
assert t.get_min_label() == 1
t.empty()
with self.assertRaises(Exception):
t.get_min_label()
def test_inorder_traversal(self) -> None:
t = self._get_binary_search_tree()
inorder_traversal_nodes = [i.label for i in t.inorder_traversal()]
assert inorder_traversal_nodes == [1, 3, 4, 5, 6, 7, 8, 10, 13, 14]
def test_preorder_traversal(self) -> None:
t = self._get_binary_search_tree()
preorder_traversal_nodes = [i.label for i in t.preorder_traversal()]
assert preorder_traversal_nodes == [8, 3, 1, 6, 4, 5, 7, 10, 14, 13]
def binary_search_tree_example() -> None:
r"""
Example
8
/ \
3 10
/ \ \
1 6 14
/ \ /
4 7 13
\
5
Example After Deletion
4
/ \
1 7
\
5
"""
t = BinarySearchTree()
t.put(8)
t.put(3)
t.put(6)
t.put(1)
t.put(10)
t.put(14)
t.put(13)
t.put(4)
t.put(7)
t.put(5)
print(
"""
8
/ \\
3 10
/ \\ \\
1 6 14
/ \\ /
4 7 13
\\
5
"""
)
print("Label 6 exists:", t.exists(6))
print("Label 13 exists:", t.exists(13))
print("Label -1 exists:", t.exists(-1))
print("Label 12 exists:", t.exists(12))
# Prints all the elements of the list in inorder traversal
inorder_traversal_nodes = [i.label for i in t.inorder_traversal()]
print("Inorder traversal:", inorder_traversal_nodes)
# Prints all the elements of the list in preorder traversal
preorder_traversal_nodes = [i.label for i in t.preorder_traversal()]
print("Preorder traversal:", preorder_traversal_nodes)
print("Max. label:", t.get_max_label())
print("Min. label:", t.get_min_label())
# Delete elements
print("\nDeleting elements 13, 10, 8, 3, 6, 14")
print(
"""
4
/ \\
1 7
\\
5
"""
)
t.remove(13)
t.remove(10)
t.remove(8)
t.remove(3)
t.remove(6)
t.remove(14)
# Prints all the elements of the list in inorder traversal after delete
inorder_traversal_nodes = [i.label for i in t.inorder_traversal()]
print("Inorder traversal after delete:", inorder_traversal_nodes)
# Prints all the elements of the list in preorder traversal after delete
preorder_traversal_nodes = [i.label for i in t.preorder_traversal()]
print("Preorder traversal after delete:", preorder_traversal_nodes)
print("Max. label:", t.get_max_label())
print("Min. label:", t.get_min_label())
if __name__ == "__main__":
binary_search_tree_example()
| """
This is a python3 implementation of binary search tree using recursion
To run tests:
python -m unittest binary_search_tree_recursive.py
To run an example:
python binary_search_tree_recursive.py
"""
import unittest
from typing import Iterator, Optional
class Node:
def __init__(self, label: int, parent: Optional["Node"]) -> None:
self.label = label
self.parent = parent
self.left: Optional[Node] = None
self.right: Optional[Node] = None
class BinarySearchTree:
def __init__(self) -> None:
self.root: Optional[Node] = None
def empty(self) -> None:
"""
Empties the tree
>>> t = BinarySearchTree()
>>> assert t.root is None
>>> t.put(8)
>>> assert t.root is not None
"""
self.root = None
def is_empty(self) -> bool:
"""
Checks if the tree is empty
>>> t = BinarySearchTree()
>>> t.is_empty()
True
>>> t.put(8)
>>> t.is_empty()
False
"""
return self.root is None
def put(self, label: int) -> None:
"""
Put a new node in the tree
>>> t = BinarySearchTree()
>>> t.put(8)
>>> assert t.root.parent is None
>>> assert t.root.label == 8
>>> t.put(10)
>>> assert t.root.right.parent == t.root
>>> assert t.root.right.label == 10
>>> t.put(3)
>>> assert t.root.left.parent == t.root
>>> assert t.root.left.label == 3
"""
self.root = self._put(self.root, label)
def _put(
self, node: Optional[Node], label: int, parent: Optional[Node] = None
) -> Node:
if node is None:
node = Node(label, parent)
else:
if label < node.label:
node.left = self._put(node.left, label, node)
elif label > node.label:
node.right = self._put(node.right, label, node)
else:
raise Exception(f"Node with label {label} already exists")
return node
def search(self, label: int) -> Node:
"""
Searches a node in the tree
>>> t = BinarySearchTree()
>>> t.put(8)
>>> t.put(10)
>>> node = t.search(8)
>>> assert node.label == 8
>>> node = t.search(3)
Traceback (most recent call last):
...
Exception: Node with label 3 does not exist
"""
return self._search(self.root, label)
def _search(self, node: Optional[Node], label: int) -> Node:
if node is None:
raise Exception(f"Node with label {label} does not exist")
else:
if label < node.label:
node = self._search(node.left, label)
elif label > node.label:
node = self._search(node.right, label)
return node
def remove(self, label: int) -> None:
"""
Removes a node in the tree
>>> t = BinarySearchTree()
>>> t.put(8)
>>> t.put(10)
>>> t.remove(8)
>>> assert t.root.label == 10
>>> t.remove(3)
Traceback (most recent call last):
...
Exception: Node with label 3 does not exist
"""
node = self.search(label)
if node.right and node.left:
lowest_node = self._get_lowest_node(node.right)
lowest_node.left = node.left
lowest_node.right = node.right
node.left.parent = lowest_node
if node.right:
node.right.parent = lowest_node
self._reassign_nodes(node, lowest_node)
elif not node.right and node.left:
self._reassign_nodes(node, node.left)
elif node.right and not node.left:
self._reassign_nodes(node, node.right)
else:
self._reassign_nodes(node, None)
def _reassign_nodes(self, node: Node, new_children: Optional[Node]) -> None:
if new_children:
new_children.parent = node.parent
if node.parent:
if node.parent.right == node:
node.parent.right = new_children
else:
node.parent.left = new_children
else:
self.root = new_children
def _get_lowest_node(self, node: Node) -> Node:
if node.left:
lowest_node = self._get_lowest_node(node.left)
else:
lowest_node = node
self._reassign_nodes(node, node.right)
return lowest_node
def exists(self, label: int) -> bool:
"""
Checks if a node exists in the tree
>>> t = BinarySearchTree()
>>> t.put(8)
>>> t.put(10)
>>> t.exists(8)
True
>>> t.exists(3)
False
"""
try:
self.search(label)
return True
except Exception:
return False
def get_max_label(self) -> int:
"""
Gets the max label inserted in the tree
>>> t = BinarySearchTree()
>>> t.get_max_label()
Traceback (most recent call last):
...
Exception: Binary search tree is empty
>>> t.put(8)
>>> t.put(10)
>>> t.get_max_label()
10
"""
if self.root is None:
raise Exception("Binary search tree is empty")
node = self.root
while node.right is not None:
node = node.right
return node.label
def get_min_label(self) -> int:
"""
Gets the min label inserted in the tree
>>> t = BinarySearchTree()
>>> t.get_min_label()
Traceback (most recent call last):
...
Exception: Binary search tree is empty
>>> t.put(8)
>>> t.put(10)
>>> t.get_min_label()
8
"""
if self.root is None:
raise Exception("Binary search tree is empty")
node = self.root
while node.left is not None:
node = node.left
return node.label
def inorder_traversal(self) -> Iterator[Node]:
"""
Return the inorder traversal of the tree
>>> t = BinarySearchTree()
>>> [i.label for i in t.inorder_traversal()]
[]
>>> t.put(8)
>>> t.put(10)
>>> t.put(9)
>>> [i.label for i in t.inorder_traversal()]
[8, 9, 10]
"""
return self._inorder_traversal(self.root)
def _inorder_traversal(self, node: Optional[Node]) -> Iterator[Node]:
if node is not None:
yield from self._inorder_traversal(node.left)
yield node
yield from self._inorder_traversal(node.right)
def preorder_traversal(self) -> Iterator[Node]:
"""
Return the preorder traversal of the tree
>>> t = BinarySearchTree()
>>> [i.label for i in t.preorder_traversal()]
[]
>>> t.put(8)
>>> t.put(10)
>>> t.put(9)
>>> [i.label for i in t.preorder_traversal()]
[8, 10, 9]
"""
return self._preorder_traversal(self.root)
def _preorder_traversal(self, node: Optional[Node]) -> Iterator[Node]:
if node is not None:
yield node
yield from self._preorder_traversal(node.left)
yield from self._preorder_traversal(node.right)
class BinarySearchTreeTest(unittest.TestCase):
@staticmethod
def _get_binary_search_tree() -> BinarySearchTree:
r"""
8
/ \
3 10
/ \ \
1 6 14
/ \ /
4 7 13
\
5
"""
t = BinarySearchTree()
t.put(8)
t.put(3)
t.put(6)
t.put(1)
t.put(10)
t.put(14)
t.put(13)
t.put(4)
t.put(7)
t.put(5)
return t
def test_put(self) -> None:
t = BinarySearchTree()
assert t.is_empty()
t.put(8)
r"""
8
"""
assert t.root is not None
assert t.root.parent is None
assert t.root.label == 8
t.put(10)
r"""
8
\
10
"""
assert t.root.right is not None
assert t.root.right.parent == t.root
assert t.root.right.label == 10
t.put(3)
r"""
8
/ \
3 10
"""
assert t.root.left is not None
assert t.root.left.parent == t.root
assert t.root.left.label == 3
t.put(6)
r"""
8
/ \
3 10
\
6
"""
assert t.root.left.right is not None
assert t.root.left.right.parent == t.root.left
assert t.root.left.right.label == 6
t.put(1)
r"""
8
/ \
3 10
/ \
1 6
"""
assert t.root.left.left is not None
assert t.root.left.left.parent == t.root.left
assert t.root.left.left.label == 1
with self.assertRaises(Exception):
t.put(1)
def test_search(self) -> None:
t = self._get_binary_search_tree()
node = t.search(6)
assert node.label == 6
node = t.search(13)
assert node.label == 13
with self.assertRaises(Exception):
t.search(2)
def test_remove(self) -> None:
t = self._get_binary_search_tree()
t.remove(13)
r"""
8
/ \
3 10
/ \ \
1 6 14
/ \
4 7
\
5
"""
assert t.root is not None
assert t.root.right is not None
assert t.root.right.right is not None
assert t.root.right.right.right is None
assert t.root.right.right.left is None
t.remove(7)
r"""
8
/ \
3 10
/ \ \
1 6 14
/
4
\
5
"""
assert t.root.left is not None
assert t.root.left.right is not None
assert t.root.left.right.left is not None
assert t.root.left.right.right is None
assert t.root.left.right.left.label == 4
t.remove(6)
r"""
8
/ \
3 10
/ \ \
1 4 14
\
5
"""
assert t.root.left.left is not None
assert t.root.left.right.right is not None
assert t.root.left.left.label == 1
assert t.root.left.right.label == 4
assert t.root.left.right.right.label == 5
assert t.root.left.right.left is None
assert t.root.left.left.parent == t.root.left
assert t.root.left.right.parent == t.root.left
t.remove(3)
r"""
8
/ \
4 10
/ \ \
1 5 14
"""
assert t.root is not None
assert t.root.left.label == 4
assert t.root.left.right.label == 5
assert t.root.left.left.label == 1
assert t.root.left.parent == t.root
assert t.root.left.left.parent == t.root.left
assert t.root.left.right.parent == t.root.left
t.remove(4)
r"""
8
/ \
5 10
/ \
1 14
"""
assert t.root.left is not None
assert t.root.left.left is not None
assert t.root.left.label == 5
assert t.root.left.right is None
assert t.root.left.left.label == 1
assert t.root.left.parent == t.root
assert t.root.left.left.parent == t.root.left
def test_remove_2(self) -> None:
t = self._get_binary_search_tree()
t.remove(3)
r"""
8
/ \
4 10
/ \ \
1 6 14
/ \ /
5 7 13
"""
assert t.root is not None
assert t.root.left is not None
assert t.root.left.left is not None
assert t.root.left.right is not None
assert t.root.left.right.left is not None
assert t.root.left.right.right is not None
assert t.root.left.label == 4
assert t.root.left.right.label == 6
assert t.root.left.left.label == 1
assert t.root.left.right.right.label == 7
assert t.root.left.right.left.label == 5
assert t.root.left.parent == t.root
assert t.root.left.right.parent == t.root.left
assert t.root.left.left.parent == t.root.left
assert t.root.left.right.left.parent == t.root.left.right
def test_empty(self) -> None:
t = self._get_binary_search_tree()
t.empty()
assert t.root is None
def test_is_empty(self) -> None:
t = self._get_binary_search_tree()
assert not t.is_empty()
t.empty()
assert t.is_empty()
def test_exists(self) -> None:
t = self._get_binary_search_tree()
assert t.exists(6)
assert not t.exists(-1)
def test_get_max_label(self) -> None:
t = self._get_binary_search_tree()
assert t.get_max_label() == 14
t.empty()
with self.assertRaises(Exception):
t.get_max_label()
def test_get_min_label(self) -> None:
t = self._get_binary_search_tree()
assert t.get_min_label() == 1
t.empty()
with self.assertRaises(Exception):
t.get_min_label()
def test_inorder_traversal(self) -> None:
t = self._get_binary_search_tree()
inorder_traversal_nodes = [i.label for i in t.inorder_traversal()]
assert inorder_traversal_nodes == [1, 3, 4, 5, 6, 7, 8, 10, 13, 14]
def test_preorder_traversal(self) -> None:
t = self._get_binary_search_tree()
preorder_traversal_nodes = [i.label for i in t.preorder_traversal()]
assert preorder_traversal_nodes == [8, 3, 1, 6, 4, 5, 7, 10, 14, 13]
def binary_search_tree_example() -> None:
r"""
Example
8
/ \
3 10
/ \ \
1 6 14
/ \ /
4 7 13
\
5
Example After Deletion
4
/ \
1 7
\
5
"""
t = BinarySearchTree()
t.put(8)
t.put(3)
t.put(6)
t.put(1)
t.put(10)
t.put(14)
t.put(13)
t.put(4)
t.put(7)
t.put(5)
print(
"""
8
/ \\
3 10
/ \\ \\
1 6 14
/ \\ /
4 7 13
\\
5
"""
)
print("Label 6 exists:", t.exists(6))
print("Label 13 exists:", t.exists(13))
print("Label -1 exists:", t.exists(-1))
print("Label 12 exists:", t.exists(12))
# Prints all the elements of the list in inorder traversal
inorder_traversal_nodes = [i.label for i in t.inorder_traversal()]
print("Inorder traversal:", inorder_traversal_nodes)
# Prints all the elements of the list in preorder traversal
preorder_traversal_nodes = [i.label for i in t.preorder_traversal()]
print("Preorder traversal:", preorder_traversal_nodes)
print("Max. label:", t.get_max_label())
print("Min. label:", t.get_min_label())
# Delete elements
print("\nDeleting elements 13, 10, 8, 3, 6, 14")
print(
"""
4
/ \\
1 7
\\
5
"""
)
t.remove(13)
t.remove(10)
t.remove(8)
t.remove(3)
t.remove(6)
t.remove(14)
# Prints all the elements of the list in inorder traversal after delete
inorder_traversal_nodes = [i.label for i in t.inorder_traversal()]
print("Inorder traversal after delete:", inorder_traversal_nodes)
# Prints all the elements of the list in preorder traversal after delete
preorder_traversal_nodes = [i.label for i in t.preorder_traversal()]
print("Preorder traversal after delete:", preorder_traversal_nodes)
print("Max. label:", t.get_max_label())
print("Min. label:", t.get_min_label())
if __name__ == "__main__":
binary_search_tree_example()
| -1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from .stack import Stack
def balanced_parentheses(parentheses: str) -> bool:
"""Use a stack to check if a string of parentheses is balanced.
>>> balanced_parentheses("([]{})")
True
>>> balanced_parentheses("[()]{}{[()()]()}")
True
>>> balanced_parentheses("[(])")
False
>>> balanced_parentheses("1+2*3-4")
True
>>> balanced_parentheses("")
True
"""
stack = Stack()
bracket_pairs = {"(": ")", "[": "]", "{": "}"}
for bracket in parentheses:
if bracket in bracket_pairs:
stack.push(bracket)
elif bracket in (")", "]", "}"):
if stack.is_empty() or bracket_pairs[stack.pop()] != bracket:
return False
return stack.is_empty()
if __name__ == "__main__":
from doctest import testmod
testmod()
examples = ["((()))", "((())", "(()))"]
print("Balanced parentheses demonstration:\n")
for example in examples:
not_str = "" if balanced_parentheses(example) else "not "
print(f"{example} is {not_str}balanced")
| from .stack import Stack
def balanced_parentheses(parentheses: str) -> bool:
"""Use a stack to check if a string of parentheses is balanced.
>>> balanced_parentheses("([]{})")
True
>>> balanced_parentheses("[()]{}{[()()]()}")
True
>>> balanced_parentheses("[(])")
False
>>> balanced_parentheses("1+2*3-4")
True
>>> balanced_parentheses("")
True
"""
stack = Stack()
bracket_pairs = {"(": ")", "[": "]", "{": "}"}
for bracket in parentheses:
if bracket in bracket_pairs:
stack.push(bracket)
elif bracket in (")", "]", "}"):
if stack.is_empty() or bracket_pairs[stack.pop()] != bracket:
return False
return stack.is_empty()
if __name__ == "__main__":
from doctest import testmod
testmod()
examples = ["((()))", "((())", "(()))"]
print("Balanced parentheses demonstration:\n")
for example in examples:
not_str = "" if balanced_parentheses(example) else "not "
print(f"{example} is {not_str}balanced")
| -1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 2: https://projecteuler.net/problem=2
Even Fibonacci Numbers
Each new term in the Fibonacci sequence is generated by adding the previous
two terms. By starting with 1 and 2, the first 10 terms will be:
1, 2, 3, 5, 8, 13, 21, 34, 55, 89, ...
By considering the terms in the Fibonacci sequence whose values do not exceed
four million, find the sum of the even-valued terms.
References:
- https://en.wikipedia.org/wiki/Fibonacci_number
"""
def solution(n: int = 4000000) -> int:
"""
Returns the sum of all even fibonacci sequence elements that are lower
or equal to n.
>>> solution(10)
10
>>> solution(15)
10
>>> solution(2)
2
>>> solution(1)
0
>>> solution(34)
44
"""
fib = [0, 1]
i = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1])
if fib[i + 2] > n:
break
i += 1
total = 0
for j in range(len(fib) - 1):
if fib[j] % 2 == 0:
total += fib[j]
return total
if __name__ == "__main__":
print(f"{solution() = }")
| """
Project Euler Problem 2: https://projecteuler.net/problem=2
Even Fibonacci Numbers
Each new term in the Fibonacci sequence is generated by adding the previous
two terms. By starting with 1 and 2, the first 10 terms will be:
1, 2, 3, 5, 8, 13, 21, 34, 55, 89, ...
By considering the terms in the Fibonacci sequence whose values do not exceed
four million, find the sum of the even-valued terms.
References:
- https://en.wikipedia.org/wiki/Fibonacci_number
"""
def solution(n: int = 4000000) -> int:
"""
Returns the sum of all even fibonacci sequence elements that are lower
or equal to n.
>>> solution(10)
10
>>> solution(15)
10
>>> solution(2)
2
>>> solution(1)
0
>>> solution(34)
44
"""
fib = [0, 1]
i = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1])
if fib[i + 2] > n:
break
i += 1
total = 0
for j in range(len(fib) - 1):
if fib[j] % 2 == 0:
total += fib[j]
return total
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Counting Sundays
Problem 19
You are given the following information, but you may prefer to do some research
for yourself.
1 Jan 1900 was a Monday.
Thirty days has September,
April, June and November.
All the rest have thirty-one,
Saving February alone,
Which has twenty-eight, rain or shine.
And on leap years, twenty-nine.
A leap year occurs on any year evenly divisible by 4, but not on a century
unless it is divisible by 400.
How many Sundays fell on the first of the month during the twentieth century
(1 Jan 1901 to 31 Dec 2000)?
"""
def solution():
"""Returns the number of mondays that fall on the first of the month during
the twentieth century (1 Jan 1901 to 31 Dec 2000)?
>>> solution()
171
"""
days_per_month = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
day = 6
month = 1
year = 1901
sundays = 0
while year < 2001:
day += 7
if (year % 4 == 0 and not year % 100 == 0) or (year % 400 == 0):
if day > days_per_month[month - 1] and month != 2:
month += 1
day = day - days_per_month[month - 2]
elif day > 29 and month == 2:
month += 1
day = day - 29
else:
if day > days_per_month[month - 1]:
month += 1
day = day - days_per_month[month - 2]
if month > 12:
year += 1
month = 1
if year < 2001 and day == 1:
sundays += 1
return sundays
if __name__ == "__main__":
print(solution())
| """
Counting Sundays
Problem 19
You are given the following information, but you may prefer to do some research
for yourself.
1 Jan 1900 was a Monday.
Thirty days has September,
April, June and November.
All the rest have thirty-one,
Saving February alone,
Which has twenty-eight, rain or shine.
And on leap years, twenty-nine.
A leap year occurs on any year evenly divisible by 4, but not on a century
unless it is divisible by 400.
How many Sundays fell on the first of the month during the twentieth century
(1 Jan 1901 to 31 Dec 2000)?
"""
def solution():
"""Returns the number of mondays that fall on the first of the month during
the twentieth century (1 Jan 1901 to 31 Dec 2000)?
>>> solution()
171
"""
days_per_month = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
day = 6
month = 1
year = 1901
sundays = 0
while year < 2001:
day += 7
if (year % 4 == 0 and not year % 100 == 0) or (year % 400 == 0):
if day > days_per_month[month - 1] and month != 2:
month += 1
day = day - days_per_month[month - 2]
elif day > 29 and month == 2:
month += 1
day = day - 29
else:
if day > days_per_month[month - 1]:
month += 1
day = day - days_per_month[month - 2]
if month > 12:
year += 1
month = 1
if year < 2001 and day == 1:
sundays += 1
return sundays
if __name__ == "__main__":
print(solution())
| -1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Coin sums
Problem 31: https://projecteuler.net/problem=31
In England the currency is made up of pound, £, and pence, p, and there are
eight coins in general circulation:
1p, 2p, 5p, 10p, 20p, 50p, £1 (100p) and £2 (200p).
It is possible to make £2 in the following way:
1×£1 + 1×50p + 2×20p + 1×5p + 1×2p + 3×1p
How many different ways can £2 be made using any number of coins?
"""
def one_pence() -> int:
return 1
def two_pence(x: int) -> int:
return 0 if x < 0 else two_pence(x - 2) + one_pence()
def five_pence(x: int) -> int:
return 0 if x < 0 else five_pence(x - 5) + two_pence(x)
def ten_pence(x: int) -> int:
return 0 if x < 0 else ten_pence(x - 10) + five_pence(x)
def twenty_pence(x: int) -> int:
return 0 if x < 0 else twenty_pence(x - 20) + ten_pence(x)
def fifty_pence(x: int) -> int:
return 0 if x < 0 else fifty_pence(x - 50) + twenty_pence(x)
def one_pound(x: int) -> int:
return 0 if x < 0 else one_pound(x - 100) + fifty_pence(x)
def two_pound(x: int) -> int:
return 0 if x < 0 else two_pound(x - 200) + one_pound(x)
def solution(n: int = 200) -> int:
"""Returns the number of different ways can n pence be made using any number of
coins?
>>> solution(500)
6295434
>>> solution(200)
73682
>>> solution(50)
451
>>> solution(10)
11
"""
return two_pound(n)
if __name__ == "__main__":
print(solution(int(input().strip())))
| """
Coin sums
Problem 31: https://projecteuler.net/problem=31
In England the currency is made up of pound, £, and pence, p, and there are
eight coins in general circulation:
1p, 2p, 5p, 10p, 20p, 50p, £1 (100p) and £2 (200p).
It is possible to make £2 in the following way:
1×£1 + 1×50p + 2×20p + 1×5p + 1×2p + 3×1p
How many different ways can £2 be made using any number of coins?
"""
def one_pence() -> int:
return 1
def two_pence(x: int) -> int:
return 0 if x < 0 else two_pence(x - 2) + one_pence()
def five_pence(x: int) -> int:
return 0 if x < 0 else five_pence(x - 5) + two_pence(x)
def ten_pence(x: int) -> int:
return 0 if x < 0 else ten_pence(x - 10) + five_pence(x)
def twenty_pence(x: int) -> int:
return 0 if x < 0 else twenty_pence(x - 20) + ten_pence(x)
def fifty_pence(x: int) -> int:
return 0 if x < 0 else fifty_pence(x - 50) + twenty_pence(x)
def one_pound(x: int) -> int:
return 0 if x < 0 else one_pound(x - 100) + fifty_pence(x)
def two_pound(x: int) -> int:
return 0 if x < 0 else two_pound(x - 200) + one_pound(x)
def solution(n: int = 200) -> int:
"""Returns the number of different ways can n pence be made using any number of
coins?
>>> solution(500)
6295434
>>> solution(200)
73682
>>> solution(50)
451
>>> solution(10)
11
"""
return two_pound(n)
if __name__ == "__main__":
print(solution(int(input().strip())))
| -1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
This is a pure Python implementation of the quick sort algorithm
For doctests run following command:
python -m doctest -v radix_sort.py
or
python3 -m doctest -v radix_sort.py
For manual testing run:
python radix_sort.py
"""
from __future__ import annotations
from typing import List
def radix_sort(list_of_ints: List[int]) -> List[int]:
"""
Examples:
>>> radix_sort([0, 5, 3, 2, 2])
[0, 2, 2, 3, 5]
>>> radix_sort(list(range(15))) == sorted(range(15))
True
>>> radix_sort(list(range(14,-1,-1))) == sorted(range(15))
True
>>> radix_sort([1,100,10,1000]) == sorted([1,100,10,1000])
True
"""
RADIX = 10
placement = 1
max_digit = max(list_of_ints)
while placement <= max_digit:
# declare and initialize empty buckets
buckets: List[list] = [list() for _ in range(RADIX)]
# split list_of_ints between the buckets
for i in list_of_ints:
tmp = int((i / placement) % RADIX)
buckets[tmp].append(i)
# put each buckets' contents into list_of_ints
a = 0
for b in range(RADIX):
for i in buckets[b]:
list_of_ints[a] = i
a += 1
# move to next
placement *= RADIX
return list_of_ints
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
This is a pure Python implementation of the quick sort algorithm
For doctests run following command:
python -m doctest -v radix_sort.py
or
python3 -m doctest -v radix_sort.py
For manual testing run:
python radix_sort.py
"""
from __future__ import annotations
from typing import List
def radix_sort(list_of_ints: List[int]) -> List[int]:
"""
Examples:
>>> radix_sort([0, 5, 3, 2, 2])
[0, 2, 2, 3, 5]
>>> radix_sort(list(range(15))) == sorted(range(15))
True
>>> radix_sort(list(range(14,-1,-1))) == sorted(range(15))
True
>>> radix_sort([1,100,10,1000]) == sorted([1,100,10,1000])
True
"""
RADIX = 10
placement = 1
max_digit = max(list_of_ints)
while placement <= max_digit:
# declare and initialize empty buckets
buckets: List[list] = [list() for _ in range(RADIX)]
# split list_of_ints between the buckets
for i in list_of_ints:
tmp = int((i / placement) % RADIX)
buckets[tmp].append(i)
# put each buckets' contents into list_of_ints
a = 0
for b in range(RADIX):
for i in buckets[b]:
list_of_ints[a] = i
a += 1
# move to next
placement *= RADIX
return list_of_ints
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
Project Euler Problem 77: https://projecteuler.net/problem=77
It is possible to write ten as the sum of primes in exactly five different ways:
7 + 3
5 + 5
5 + 3 + 2
3 + 3 + 2 + 2
2 + 2 + 2 + 2 + 2
What is the first value which can be written as the sum of primes in over
five thousand different ways?
"""
from functools import lru_cache
from math import ceil
from typing import Optional, Set
NUM_PRIMES = 100
primes = set(range(3, NUM_PRIMES, 2))
primes.add(2)
prime: int
for prime in range(3, ceil(NUM_PRIMES ** 0.5), 2):
if prime not in primes:
continue
primes.difference_update(set(range(prime * prime, NUM_PRIMES, prime)))
@lru_cache(maxsize=100)
def partition(number_to_partition: int) -> Set[int]:
"""
Return a set of integers corresponding to unique prime partitions of n.
The unique prime partitions can be represented as unique prime decompositions,
e.g. (7+3) <-> 7*3 = 12, (3+3+2+2) = 3*3*2*2 = 36
>>> partition(10)
{32, 36, 21, 25, 30}
>>> partition(15)
{192, 160, 105, 44, 112, 243, 180, 150, 216, 26, 125, 126}
>>> len(partition(20))
26
"""
if number_to_partition < 0:
return set()
elif number_to_partition == 0:
return {1}
ret: Set[int] = set()
prime: int
sub: int
for prime in primes:
if prime > number_to_partition:
continue
for sub in partition(number_to_partition - prime):
ret.add(sub * prime)
return ret
def solution(number_unique_partitions: int = 5000) -> Optional[int]:
"""
Return the smallest integer that can be written as the sum of primes in over
m unique ways.
>>> solution(4)
10
>>> solution(500)
45
>>> solution(1000)
53
"""
for number_to_partition in range(1, NUM_PRIMES):
if len(partition(number_to_partition)) > number_unique_partitions:
return number_to_partition
return None
if __name__ == "__main__":
print(f"{solution() = }")
| """
Project Euler Problem 77: https://projecteuler.net/problem=77
It is possible to write ten as the sum of primes in exactly five different ways:
7 + 3
5 + 5
5 + 3 + 2
3 + 3 + 2 + 2
2 + 2 + 2 + 2 + 2
What is the first value which can be written as the sum of primes in over
five thousand different ways?
"""
from functools import lru_cache
from math import ceil
from typing import Optional, Set
NUM_PRIMES = 100
primes = set(range(3, NUM_PRIMES, 2))
primes.add(2)
prime: int
for prime in range(3, ceil(NUM_PRIMES ** 0.5), 2):
if prime not in primes:
continue
primes.difference_update(set(range(prime * prime, NUM_PRIMES, prime)))
@lru_cache(maxsize=100)
def partition(number_to_partition: int) -> Set[int]:
"""
Return a set of integers corresponding to unique prime partitions of n.
The unique prime partitions can be represented as unique prime decompositions,
e.g. (7+3) <-> 7*3 = 12, (3+3+2+2) = 3*3*2*2 = 36
>>> partition(10)
{32, 36, 21, 25, 30}
>>> partition(15)
{192, 160, 105, 44, 112, 243, 180, 150, 216, 26, 125, 126}
>>> len(partition(20))
26
"""
if number_to_partition < 0:
return set()
elif number_to_partition == 0:
return {1}
ret: Set[int] = set()
prime: int
sub: int
for prime in primes:
if prime > number_to_partition:
continue
for sub in partition(number_to_partition - prime):
ret.add(sub * prime)
return ret
def solution(number_unique_partitions: int = 5000) -> Optional[int]:
"""
Return the smallest integer that can be written as the sum of primes in over
m unique ways.
>>> solution(4)
10
>>> solution(500)
45
>>> solution(1000)
53
"""
for number_to_partition in range(1, NUM_PRIMES):
if len(partition(number_to_partition)) > number_unique_partitions:
return number_to_partition
return None
if __name__ == "__main__":
print(f"{solution() = }")
| -1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| def lower(word: str) -> str:
"""
Will convert the entire string to lowercase letters
>>> lower("wow")
'wow'
>>> lower("HellZo")
'hellzo'
>>> lower("WHAT")
'what'
>>> lower("wh[]32")
'wh[]32'
>>> lower("whAT")
'what'
"""
# converting to ascii value int value and checking to see if char is a capital
# letter if it is a capital letter it is getting shift by 32 which makes it a lower
# case letter
return "".join(chr(ord(char) + 32) if "A" <= char <= "Z" else char for char in word)
if __name__ == "__main__":
from doctest import testmod
testmod()
| def lower(word: str) -> str:
"""
Will convert the entire string to lowercase letters
>>> lower("wow")
'wow'
>>> lower("HellZo")
'hellzo'
>>> lower("WHAT")
'what'
>>> lower("wh[]32")
'wh[]32'
>>> lower("whAT")
'what'
"""
# converting to ascii value int value and checking to see if char is a capital
# letter if it is a capital letter it is getting shift by 32 which makes it a lower
# case letter
return "".join(chr(ord(char) + 32) if "A" <= char <= "Z" else char for char in word)
if __name__ == "__main__":
from doctest import testmod
testmod()
| -1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| -1 |
||
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
This is a type of divide and conquer algorithm which divides the search space into
3 parts and finds the target value based on the property of the array or list
(usually monotonic property).
Time Complexity : O(log3 N)
Space Complexity : O(1)
"""
from typing import List
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
precision = 10
# This is the linear search that will occur after the search space has become smaller.
def lin_search(left: int, right: int, array: List[int], target: int) -> int:
"""Perform linear search in list. Returns -1 if element is not found.
Parameters
----------
left : int
left index bound.
right : int
right index bound.
array : List[int]
List of elements to be searched on
target : int
Element that is searched
Returns
-------
int
index of element that is looked for.
Examples
--------
>>> lin_search(0, 4, [4, 5, 6, 7], 7)
3
>>> lin_search(0, 3, [4, 5, 6, 7], 7)
-1
>>> lin_search(0, 2, [-18, 2], -18)
0
>>> lin_search(0, 1, [5], 5)
0
>>> lin_search(0, 3, ['a', 'c', 'd'], 'c')
1
>>> lin_search(0, 3, [.1, .4 , -.1], .1)
0
>>> lin_search(0, 3, [.1, .4 , -.1], -.1)
2
"""
for i in range(left, right):
if array[i] == target:
return i
return -1
def ite_ternary_search(array: List[int], target: int) -> int:
"""Iterative method of the ternary search algorithm.
>>> test_list = [0, 1, 2, 8, 13, 17, 19, 32, 42]
>>> ite_ternary_search(test_list, 3)
-1
>>> ite_ternary_search(test_list, 13)
4
>>> ite_ternary_search([4, 5, 6, 7], 4)
0
>>> ite_ternary_search([4, 5, 6, 7], -10)
-1
>>> ite_ternary_search([-18, 2], -18)
0
>>> ite_ternary_search([5], 5)
0
>>> ite_ternary_search(['a', 'c', 'd'], 'c')
1
>>> ite_ternary_search(['a', 'c', 'd'], 'f')
-1
>>> ite_ternary_search([], 1)
-1
>>> ite_ternary_search([.1, .4 , -.1], .1)
0
"""
left = 0
right = len(array)
while left <= right:
if right - left < precision:
return lin_search(left, right, array, target)
one_third = (left + right) / 3 + 1
two_third = 2 * (left + right) / 3 + 1
if array[one_third] == target:
return one_third
elif array[two_third] == target:
return two_third
elif target < array[one_third]:
right = one_third - 1
elif array[two_third] < target:
left = two_third + 1
else:
left = one_third + 1
right = two_third - 1
else:
return -1
def rec_ternary_search(left: int, right: int, array: List[int], target: int) -> int:
"""Recursive method of the ternary search algorithm.
>>> test_list = [0, 1, 2, 8, 13, 17, 19, 32, 42]
>>> rec_ternary_search(0, len(test_list), test_list, 3)
-1
>>> rec_ternary_search(4, len(test_list), test_list, 42)
8
>>> rec_ternary_search(0, 2, [4, 5, 6, 7], 4)
0
>>> rec_ternary_search(0, 3, [4, 5, 6, 7], -10)
-1
>>> rec_ternary_search(0, 1, [-18, 2], -18)
0
>>> rec_ternary_search(0, 1, [5], 5)
0
>>> rec_ternary_search(0, 2, ['a', 'c', 'd'], 'c')
1
>>> rec_ternary_search(0, 2, ['a', 'c', 'd'], 'f')
-1
>>> rec_ternary_search(0, 0, [], 1)
-1
>>> rec_ternary_search(0, 3, [.1, .4 , -.1], .1)
0
"""
if left < right:
if right - left < precision:
return lin_search(left, right, array, target)
one_third = (left + right) / 3 + 1
two_third = 2 * (left + right) / 3 + 1
if array[one_third] == target:
return one_third
elif array[two_third] == target:
return two_third
elif target < array[one_third]:
return rec_ternary_search(left, one_third - 1, array, target)
elif array[two_third] < target:
return rec_ternary_search(two_third + 1, right, array, target)
else:
return rec_ternary_search(one_third + 1, two_third - 1, array, target)
else:
return -1
if __name__ == "__main__":
user_input = input("Enter numbers separated by comma:\n").strip()
collection = [int(item.strip()) for item in user_input.split(",")]
assert collection == sorted(collection), f"List must be ordered.\n{collection}."
target = int(input("Enter the number to be found in the list:\n").strip())
result1 = ite_ternary_search(collection, target)
result2 = rec_ternary_search(0, len(collection) - 1, collection, target)
if result2 != -1:
print(f"Iterative search: {target} found at positions: {result1}")
print(f"Recursive search: {target} found at positions: {result2}")
else:
print("Not found")
| """
This is a type of divide and conquer algorithm which divides the search space into
3 parts and finds the target value based on the property of the array or list
(usually monotonic property).
Time Complexity : O(log3 N)
Space Complexity : O(1)
"""
from typing import List
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
precision = 10
# This is the linear search that will occur after the search space has become smaller.
def lin_search(left: int, right: int, array: List[int], target: int) -> int:
"""Perform linear search in list. Returns -1 if element is not found.
Parameters
----------
left : int
left index bound.
right : int
right index bound.
array : List[int]
List of elements to be searched on
target : int
Element that is searched
Returns
-------
int
index of element that is looked for.
Examples
--------
>>> lin_search(0, 4, [4, 5, 6, 7], 7)
3
>>> lin_search(0, 3, [4, 5, 6, 7], 7)
-1
>>> lin_search(0, 2, [-18, 2], -18)
0
>>> lin_search(0, 1, [5], 5)
0
>>> lin_search(0, 3, ['a', 'c', 'd'], 'c')
1
>>> lin_search(0, 3, [.1, .4 , -.1], .1)
0
>>> lin_search(0, 3, [.1, .4 , -.1], -.1)
2
"""
for i in range(left, right):
if array[i] == target:
return i
return -1
def ite_ternary_search(array: List[int], target: int) -> int:
"""Iterative method of the ternary search algorithm.
>>> test_list = [0, 1, 2, 8, 13, 17, 19, 32, 42]
>>> ite_ternary_search(test_list, 3)
-1
>>> ite_ternary_search(test_list, 13)
4
>>> ite_ternary_search([4, 5, 6, 7], 4)
0
>>> ite_ternary_search([4, 5, 6, 7], -10)
-1
>>> ite_ternary_search([-18, 2], -18)
0
>>> ite_ternary_search([5], 5)
0
>>> ite_ternary_search(['a', 'c', 'd'], 'c')
1
>>> ite_ternary_search(['a', 'c', 'd'], 'f')
-1
>>> ite_ternary_search([], 1)
-1
>>> ite_ternary_search([.1, .4 , -.1], .1)
0
"""
left = 0
right = len(array)
while left <= right:
if right - left < precision:
return lin_search(left, right, array, target)
one_third = (left + right) / 3 + 1
two_third = 2 * (left + right) / 3 + 1
if array[one_third] == target:
return one_third
elif array[two_third] == target:
return two_third
elif target < array[one_third]:
right = one_third - 1
elif array[two_third] < target:
left = two_third + 1
else:
left = one_third + 1
right = two_third - 1
else:
return -1
def rec_ternary_search(left: int, right: int, array: List[int], target: int) -> int:
"""Recursive method of the ternary search algorithm.
>>> test_list = [0, 1, 2, 8, 13, 17, 19, 32, 42]
>>> rec_ternary_search(0, len(test_list), test_list, 3)
-1
>>> rec_ternary_search(4, len(test_list), test_list, 42)
8
>>> rec_ternary_search(0, 2, [4, 5, 6, 7], 4)
0
>>> rec_ternary_search(0, 3, [4, 5, 6, 7], -10)
-1
>>> rec_ternary_search(0, 1, [-18, 2], -18)
0
>>> rec_ternary_search(0, 1, [5], 5)
0
>>> rec_ternary_search(0, 2, ['a', 'c', 'd'], 'c')
1
>>> rec_ternary_search(0, 2, ['a', 'c', 'd'], 'f')
-1
>>> rec_ternary_search(0, 0, [], 1)
-1
>>> rec_ternary_search(0, 3, [.1, .4 , -.1], .1)
0
"""
if left < right:
if right - left < precision:
return lin_search(left, right, array, target)
one_third = (left + right) / 3 + 1
two_third = 2 * (left + right) / 3 + 1
if array[one_third] == target:
return one_third
elif array[two_third] == target:
return two_third
elif target < array[one_third]:
return rec_ternary_search(left, one_third - 1, array, target)
elif array[two_third] < target:
return rec_ternary_search(two_third + 1, right, array, target)
else:
return rec_ternary_search(one_third + 1, two_third - 1, array, target)
else:
return -1
if __name__ == "__main__":
user_input = input("Enter numbers separated by comma:\n").strip()
collection = [int(item.strip()) for item in user_input.split(",")]
assert collection == sorted(collection), f"List must be ordered.\n{collection}."
target = int(input("Enter the number to be found in the list:\n").strip())
result1 = ite_ternary_search(collection, target)
result2 = rec_ternary_search(0, len(collection) - 1, collection, target)
if result2 != -1:
print(f"Iterative search: {target} found at positions: {result1}")
print(f"Recursive search: {target} found at positions: {result2}")
else:
print("Not found")
| -1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| # https://www.geeksforgeeks.org/newton-forward-backward-interpolation/
import math
from typing import List
# for calculating u value
def ucal(u: float, p: int) -> float:
"""
>>> ucal(1, 2)
0
>>> ucal(1.1, 2)
0.11000000000000011
>>> ucal(1.2, 2)
0.23999999999999994
"""
temp = u
for i in range(1, p):
temp = temp * (u - i)
return temp
def main() -> None:
n = int(input("enter the numbers of values: "))
y: List[List[float]] = []
for i in range(n):
y.append([])
for i in range(n):
for j in range(n):
y[i].append(j)
y[i][j] = 0
print("enter the values of parameters in a list: ")
x = list(map(int, input().split()))
print("enter the values of corresponding parameters: ")
for i in range(n):
y[i][0] = float(input())
value = int(input("enter the value to interpolate: "))
u = (value - x[0]) / (x[1] - x[0])
# for calculating forward difference table
for i in range(1, n):
for j in range(n - i):
y[j][i] = y[j + 1][i - 1] - y[j][i - 1]
summ = y[0][0]
for i in range(1, n):
summ += (ucal(u, i) * y[0][i]) / math.factorial(i)
print(f"the value at {value} is {summ}")
if __name__ == "__main__":
main()
| # https://www.geeksforgeeks.org/newton-forward-backward-interpolation/
import math
from typing import List
# for calculating u value
def ucal(u: float, p: int) -> float:
"""
>>> ucal(1, 2)
0
>>> ucal(1.1, 2)
0.11000000000000011
>>> ucal(1.2, 2)
0.23999999999999994
"""
temp = u
for i in range(1, p):
temp = temp * (u - i)
return temp
def main() -> None:
n = int(input("enter the numbers of values: "))
y: List[List[float]] = []
for i in range(n):
y.append([])
for i in range(n):
for j in range(n):
y[i].append(j)
y[i][j] = 0
print("enter the values of parameters in a list: ")
x = list(map(int, input().split()))
print("enter the values of corresponding parameters: ")
for i in range(n):
y[i][0] = float(input())
value = int(input("enter the value to interpolate: "))
u = (value - x[0]) / (x[1] - x[0])
# for calculating forward difference table
for i in range(1, n):
for j in range(n - i):
y[j][i] = y[j + 1][i - 1] - y[j][i - 1]
summ = y[0][0]
for i in range(1, n):
summ += (ucal(u, i) * y[0][i]) / math.factorial(i)
print(f"the value at {value} is {summ}")
if __name__ == "__main__":
main()
| -1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """Conway's Game Of Life, Author Anurag Kumar(mailto:[email protected])
Requirements:
- numpy
- random
- time
- matplotlib
Python:
- 3.5
Usage:
- $python3 game_o_life <canvas_size:int>
Game-Of-Life Rules:
1.
Any live cell with fewer than two live neighbours
dies, as if caused by under-population.
2.
Any live cell with two or three live neighbours lives
on to the next generation.
3.
Any live cell with more than three live neighbours
dies, as if by over-population.
4.
Any dead cell with exactly three live neighbours be-
comes a live cell, as if by reproduction.
"""
import random
import sys
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
usage_doc = "Usage of script: script_nama <size_of_canvas:int>"
choice = [0] * 100 + [1] * 10
random.shuffle(choice)
def create_canvas(size):
canvas = [[False for i in range(size)] for j in range(size)]
return canvas
def seed(canvas):
for i, row in enumerate(canvas):
for j, _ in enumerate(row):
canvas[i][j] = bool(random.getrandbits(1))
def run(canvas):
"""This function runs the rules of game through all points, and changes their
status accordingly.(in the same canvas)
@Args:
--
canvas : canvas of population to run the rules on.
@returns:
--
None
"""
canvas = np.array(canvas)
next_gen_canvas = np.array(create_canvas(canvas.shape[0]))
for r, row in enumerate(canvas):
for c, pt in enumerate(row):
# print(r-1,r+2,c-1,c+2)
next_gen_canvas[r][c] = __judge_point(
pt, canvas[r - 1 : r + 2, c - 1 : c + 2]
)
canvas = next_gen_canvas
del next_gen_canvas # cleaning memory as we move on.
return canvas.tolist()
def __judge_point(pt, neighbours):
dead = 0
alive = 0
# finding dead or alive neighbours count.
for i in neighbours:
for status in i:
if status:
alive += 1
else:
dead += 1
# handling duplicate entry for focus pt.
if pt:
alive -= 1
else:
dead -= 1
# running the rules of game here.
state = pt
if pt:
if alive < 2:
state = False
elif alive == 2 or alive == 3:
state = True
elif alive > 3:
state = False
else:
if alive == 3:
state = True
return state
if __name__ == "__main__":
if len(sys.argv) != 2:
raise Exception(usage_doc)
canvas_size = int(sys.argv[1])
# main working structure of this module.
c = create_canvas(canvas_size)
seed(c)
fig, ax = plt.subplots()
fig.show()
cmap = ListedColormap(["w", "k"])
try:
while True:
c = run(c)
ax.matshow(c, cmap=cmap)
fig.canvas.draw()
ax.cla()
except KeyboardInterrupt:
# do nothing.
pass
| """Conway's Game Of Life, Author Anurag Kumar(mailto:[email protected])
Requirements:
- numpy
- random
- time
- matplotlib
Python:
- 3.5
Usage:
- $python3 game_o_life <canvas_size:int>
Game-Of-Life Rules:
1.
Any live cell with fewer than two live neighbours
dies, as if caused by under-population.
2.
Any live cell with two or three live neighbours lives
on to the next generation.
3.
Any live cell with more than three live neighbours
dies, as if by over-population.
4.
Any dead cell with exactly three live neighbours be-
comes a live cell, as if by reproduction.
"""
import random
import sys
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.colors import ListedColormap
usage_doc = "Usage of script: script_nama <size_of_canvas:int>"
choice = [0] * 100 + [1] * 10
random.shuffle(choice)
def create_canvas(size):
canvas = [[False for i in range(size)] for j in range(size)]
return canvas
def seed(canvas):
for i, row in enumerate(canvas):
for j, _ in enumerate(row):
canvas[i][j] = bool(random.getrandbits(1))
def run(canvas):
"""This function runs the rules of game through all points, and changes their
status accordingly.(in the same canvas)
@Args:
--
canvas : canvas of population to run the rules on.
@returns:
--
None
"""
canvas = np.array(canvas)
next_gen_canvas = np.array(create_canvas(canvas.shape[0]))
for r, row in enumerate(canvas):
for c, pt in enumerate(row):
# print(r-1,r+2,c-1,c+2)
next_gen_canvas[r][c] = __judge_point(
pt, canvas[r - 1 : r + 2, c - 1 : c + 2]
)
canvas = next_gen_canvas
del next_gen_canvas # cleaning memory as we move on.
return canvas.tolist()
def __judge_point(pt, neighbours):
dead = 0
alive = 0
# finding dead or alive neighbours count.
for i in neighbours:
for status in i:
if status:
alive += 1
else:
dead += 1
# handling duplicate entry for focus pt.
if pt:
alive -= 1
else:
dead -= 1
# running the rules of game here.
state = pt
if pt:
if alive < 2:
state = False
elif alive == 2 or alive == 3:
state = True
elif alive > 3:
state = False
else:
if alive == 3:
state = True
return state
if __name__ == "__main__":
if len(sys.argv) != 2:
raise Exception(usage_doc)
canvas_size = int(sys.argv[1])
# main working structure of this module.
c = create_canvas(canvas_size)
seed(c)
fig, ax = plt.subplots()
fig.show()
cmap = ListedColormap(["w", "k"])
try:
while True:
c = run(c)
ax.matshow(c, cmap=cmap)
fig.canvas.draw()
ax.cla()
except KeyboardInterrupt:
# do nothing.
pass
| -1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| import sys
from abc import abstractmethod
from collections import deque
class LRUCache:
"""Page Replacement Algorithm, Least Recently Used (LRU) Caching."""
dq_store = object() # Cache store of keys
key_reference_map = object() # References of the keys in cache
_MAX_CAPACITY: int = 10 # Maximum capacity of cache
@abstractmethod
def __init__(self, n: int):
"""Creates an empty store and map for the keys.
The LRUCache is set the size n.
"""
self.dq_store = deque()
self.key_reference_map = set()
if not n:
LRUCache._MAX_CAPACITY = sys.maxsize
elif n < 0:
raise ValueError("n should be an integer greater than 0.")
else:
LRUCache._MAX_CAPACITY = n
def refer(self, x):
"""
Looks for a page in the cache store and adds reference to the set.
Remove the least recently used key if the store is full.
Update store to reflect recent access.
"""
if x not in self.key_reference_map:
if len(self.dq_store) == LRUCache._MAX_CAPACITY:
last_element = self.dq_store.pop()
self.key_reference_map.remove(last_element)
else:
index_remove = 0
for idx, key in enumerate(self.dq_store):
if key == x:
index_remove = idx
break
self.dq_store.remove(index_remove)
self.dq_store.appendleft(x)
self.key_reference_map.add(x)
def display(self):
"""
Prints all the elements in the store.
"""
for k in self.dq_store:
print(k)
if __name__ == "__main__":
lru_cache = LRUCache(4)
lru_cache.refer(1)
lru_cache.refer(2)
lru_cache.refer(3)
lru_cache.refer(1)
lru_cache.refer(4)
lru_cache.refer(5)
lru_cache.display()
| import sys
from abc import abstractmethod
from collections import deque
class LRUCache:
"""Page Replacement Algorithm, Least Recently Used (LRU) Caching."""
dq_store = object() # Cache store of keys
key_reference_map = object() # References of the keys in cache
_MAX_CAPACITY: int = 10 # Maximum capacity of cache
@abstractmethod
def __init__(self, n: int):
"""Creates an empty store and map for the keys.
The LRUCache is set the size n.
"""
self.dq_store = deque()
self.key_reference_map = set()
if not n:
LRUCache._MAX_CAPACITY = sys.maxsize
elif n < 0:
raise ValueError("n should be an integer greater than 0.")
else:
LRUCache._MAX_CAPACITY = n
def refer(self, x):
"""
Looks for a page in the cache store and adds reference to the set.
Remove the least recently used key if the store is full.
Update store to reflect recent access.
"""
if x not in self.key_reference_map:
if len(self.dq_store) == LRUCache._MAX_CAPACITY:
last_element = self.dq_store.pop()
self.key_reference_map.remove(last_element)
else:
index_remove = 0
for idx, key in enumerate(self.dq_store):
if key == x:
index_remove = idx
break
self.dq_store.remove(index_remove)
self.dq_store.appendleft(x)
self.key_reference_map.add(x)
def display(self):
"""
Prints all the elements in the store.
"""
for k in self.dq_store:
print(k)
if __name__ == "__main__":
lru_cache = LRUCache(4)
lru_cache.refer(1)
lru_cache.refer(2)
lru_cache.refer(3)
lru_cache.refer(1)
lru_cache.refer(4)
lru_cache.refer(5)
lru_cache.display()
| -1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """ Multiply two numbers using Karatsuba algorithm """
def karatsuba(a, b):
"""
>>> karatsuba(15463, 23489) == 15463 * 23489
True
>>> karatsuba(3, 9) == 3 * 9
True
"""
if len(str(a)) == 1 or len(str(b)) == 1:
return a * b
else:
m1 = max(len(str(a)), len(str(b)))
m2 = m1 // 2
a1, a2 = divmod(a, 10 ** m2)
b1, b2 = divmod(b, 10 ** m2)
x = karatsuba(a2, b2)
y = karatsuba((a1 + a2), (b1 + b2))
z = karatsuba(a1, b1)
return (z * 10 ** (2 * m2)) + ((y - z - x) * 10 ** (m2)) + (x)
def main():
print(karatsuba(15463, 23489))
if __name__ == "__main__":
main()
| """ Multiply two numbers using Karatsuba algorithm """
def karatsuba(a, b):
"""
>>> karatsuba(15463, 23489) == 15463 * 23489
True
>>> karatsuba(3, 9) == 3 * 9
True
"""
if len(str(a)) == 1 or len(str(b)) == 1:
return a * b
else:
m1 = max(len(str(a)), len(str(b)))
m2 = m1 // 2
a1, a2 = divmod(a, 10 ** m2)
b1, b2 = divmod(b, 10 ** m2)
x = karatsuba(a2, b2)
y = karatsuba((a1 + a2), (b1 + b2))
z = karatsuba(a1, b1)
return (z * 10 ** (2 * m2)) + ((y - z - x) * 10 ** (m2)) + (x)
def main():
print(karatsuba(15463, 23489))
if __name__ == "__main__":
main()
| -1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| import sys
import webbrowser
import requests
from bs4 import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print("Googling.....")
url = "https://www.google.com/search?q=" + " ".join(sys.argv[1:])
res = requests.get(url, headers={"UserAgent": UserAgent().random})
# res.raise_for_status()
with open("project1a.html", "wb") as out_file: # only for knowing the class
for data in res.iter_content(10000):
out_file.write(data)
soup = BeautifulSoup(res.text, "html.parser")
links = list(soup.select(".eZt8xd"))[:5]
print(len(links))
for link in links:
if link.text == "Maps":
webbrowser.open(link.get("href"))
else:
webbrowser.open(f"http://google.com{link.get('href')}")
| import sys
import webbrowser
import requests
from bs4 import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print("Googling.....")
url = "https://www.google.com/search?q=" + " ".join(sys.argv[1:])
res = requests.get(url, headers={"UserAgent": UserAgent().random})
# res.raise_for_status()
with open("project1a.html", "wb") as out_file: # only for knowing the class
for data in res.iter_content(10000):
out_file.write(data)
soup = BeautifulSoup(res.text, "html.parser")
links = list(soup.select(".eZt8xd"))[:5]
print(len(links))
for link in links:
if link.text == "Maps":
webbrowser.open(link.get("href"))
else:
webbrowser.open(f"http://google.com{link.get('href')}")
| -1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| from typing import List
def merge(left_half: List, right_half: List) -> List:
"""Helper function for mergesort.
>>> left_half = [-2]
>>> right_half = [-1]
>>> merge(left_half, right_half)
[-2, -1]
>>> left_half = [1,2,3]
>>> right_half = [4,5,6]
>>> merge(left_half, right_half)
[1, 2, 3, 4, 5, 6]
>>> left_half = [-2]
>>> right_half = [-1]
>>> merge(left_half, right_half)
[-2, -1]
>>> left_half = [12, 15]
>>> right_half = [13, 14]
>>> merge(left_half, right_half)
[12, 13, 14, 15]
>>> left_half = []
>>> right_half = []
>>> merge(left_half, right_half)
[]
"""
sorted_array = [None] * (len(right_half) + len(left_half))
pointer1 = 0 # pointer to current index for left Half
pointer2 = 0 # pointer to current index for the right Half
index = 0 # pointer to current index for the sorted array Half
while pointer1 < len(left_half) and pointer2 < len(right_half):
if left_half[pointer1] < right_half[pointer2]:
sorted_array[index] = left_half[pointer1]
pointer1 += 1
index += 1
else:
sorted_array[index] = right_half[pointer2]
pointer2 += 1
index += 1
while pointer1 < len(left_half):
sorted_array[index] = left_half[pointer1]
pointer1 += 1
index += 1
while pointer2 < len(right_half):
sorted_array[index] = right_half[pointer2]
pointer2 += 1
index += 1
return sorted_array
def merge_sort(array: List) -> List:
"""Returns a list of sorted array elements using merge sort.
>>> from random import shuffle
>>> array = [-2, 3, -10, 11, 99, 100000, 100, -200]
>>> shuffle(array)
>>> merge_sort(array)
[-200, -10, -2, 3, 11, 99, 100, 100000]
>>> shuffle(array)
>>> merge_sort(array)
[-200, -10, -2, 3, 11, 99, 100, 100000]
>>> array = [-200]
>>> merge_sort(array)
[-200]
>>> array = [-2, 3, -10, 11, 99, 100000, 100, -200]
>>> shuffle(array)
>>> sorted(array) == merge_sort(array)
True
>>> array = [-2]
>>> merge_sort(array)
[-2]
>>> array = []
>>> merge_sort(array)
[]
>>> array = [10000000, 1, -1111111111, 101111111112, 9000002]
>>> sorted(array) == merge_sort(array)
True
"""
if len(array) <= 1:
return array
# the actual formula to calculate the middle element = left + (right - left) // 2
# this avoids integer overflow in case of large N
middle = 0 + (len(array) - 0) // 2
# Split the array into halves till the array length becomes equal to One
# merge the arrays of single length returned by mergeSort function and
# pass them into the merge arrays function which merges the array
left_half = array[:middle]
right_half = array[middle:]
return merge(merge_sort(left_half), merge_sort(right_half))
if __name__ == "__main__":
import doctest
doctest.testmod()
| from typing import List
def merge(left_half: List, right_half: List) -> List:
"""Helper function for mergesort.
>>> left_half = [-2]
>>> right_half = [-1]
>>> merge(left_half, right_half)
[-2, -1]
>>> left_half = [1,2,3]
>>> right_half = [4,5,6]
>>> merge(left_half, right_half)
[1, 2, 3, 4, 5, 6]
>>> left_half = [-2]
>>> right_half = [-1]
>>> merge(left_half, right_half)
[-2, -1]
>>> left_half = [12, 15]
>>> right_half = [13, 14]
>>> merge(left_half, right_half)
[12, 13, 14, 15]
>>> left_half = []
>>> right_half = []
>>> merge(left_half, right_half)
[]
"""
sorted_array = [None] * (len(right_half) + len(left_half))
pointer1 = 0 # pointer to current index for left Half
pointer2 = 0 # pointer to current index for the right Half
index = 0 # pointer to current index for the sorted array Half
while pointer1 < len(left_half) and pointer2 < len(right_half):
if left_half[pointer1] < right_half[pointer2]:
sorted_array[index] = left_half[pointer1]
pointer1 += 1
index += 1
else:
sorted_array[index] = right_half[pointer2]
pointer2 += 1
index += 1
while pointer1 < len(left_half):
sorted_array[index] = left_half[pointer1]
pointer1 += 1
index += 1
while pointer2 < len(right_half):
sorted_array[index] = right_half[pointer2]
pointer2 += 1
index += 1
return sorted_array
def merge_sort(array: List) -> List:
"""Returns a list of sorted array elements using merge sort.
>>> from random import shuffle
>>> array = [-2, 3, -10, 11, 99, 100000, 100, -200]
>>> shuffle(array)
>>> merge_sort(array)
[-200, -10, -2, 3, 11, 99, 100, 100000]
>>> shuffle(array)
>>> merge_sort(array)
[-200, -10, -2, 3, 11, 99, 100, 100000]
>>> array = [-200]
>>> merge_sort(array)
[-200]
>>> array = [-2, 3, -10, 11, 99, 100000, 100, -200]
>>> shuffle(array)
>>> sorted(array) == merge_sort(array)
True
>>> array = [-2]
>>> merge_sort(array)
[-2]
>>> array = []
>>> merge_sort(array)
[]
>>> array = [10000000, 1, -1111111111, 101111111112, 9000002]
>>> sorted(array) == merge_sort(array)
True
"""
if len(array) <= 1:
return array
# the actual formula to calculate the middle element = left + (right - left) // 2
# this avoids integer overflow in case of large N
middle = 0 + (len(array) - 0) // 2
# Split the array into halves till the array length becomes equal to One
# merge the arrays of single length returned by mergeSort function and
# pass them into the merge arrays function which merges the array
left_half = array[:middle]
right_half = array[middle:]
return merge(merge_sort(left_half), merge_sort(right_half))
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
TheAlgorithms/Python | 4,267 | Wavelet tree | ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| anirudnits | 2021-03-14T09:36:53Z | 2021-06-08T20:49:33Z | f37d415227a21017398144a090a66f1c690705eb | b743e442599a5bf7e1cb14d9dc41bd17bde1504c | Wavelet tree. ### **Describe your change:**
* [x] Add an algorithm?
* [ ] Fix a bug or typo in an existing algorithm?
* [ ] Documentation change?
### **Checklist:**
* [x] I have read [CONTRIBUTING.md](https://github.com/TheAlgorithms/Python/blob/master/CONTRIBUTING.md).
* [x] This pull request is all my own work -- I have not plagiarized.
* [x] I know that pull requests will not be merged if they fail the automated tests.
* [x] This PR only changes one algorithm file. To ease review, please open separate PRs for separate algorithms.
* [x] All new Python files are placed inside an existing directory.
* [x] All filenames are in all lowercase characters with no spaces or dashes.
* [x] All functions and variable names follow Python naming conventions.
* [x] All function parameters and return values are annotated with Python [type hints](https://docs.python.org/3/library/typing.html).
* [x] All functions have [doctests](https://docs.python.org/3/library/doctest.html) that pass the automated testing.
* [x] All new algorithms have a URL in its comments that points to Wikipedia or other similar explanation.
* [ ] If this pull request resolves one or more open issues then the commit message contains `Fixes: #{$ISSUE_NO}`.
| """
@author: MatteoRaso
"""
from math import pi, sqrt
from random import uniform
from statistics import mean
from typing import Callable
def pi_estimator(iterations: int):
"""
An implementation of the Monte Carlo method used to find pi.
1. Draw a 2x2 square centred at (0,0).
2. Inscribe a circle within the square.
3. For each iteration, place a dot anywhere in the square.
a. Record the number of dots within the circle.
4. After all the dots are placed, divide the dots in the circle by the total.
5. Multiply this value by 4 to get your estimate of pi.
6. Print the estimated and numpy value of pi
"""
# A local function to see if a dot lands in the circle.
def is_in_circle(x: float, y: float) -> bool:
distance_from_centre = sqrt((x ** 2) + (y ** 2))
# Our circle has a radius of 1, so a distance
# greater than 1 would land outside the circle.
return distance_from_centre <= 1
# The proportion of guesses that landed in the circle
proportion = mean(
int(is_in_circle(uniform(-1.0, 1.0), uniform(-1.0, 1.0)))
for _ in range(iterations)
)
# The ratio of the area for circle to square is pi/4.
pi_estimate = proportion * 4
print(f"The estimated value of pi is {pi_estimate}")
print(f"The numpy value of pi is {pi}")
print(f"The total error is {abs(pi - pi_estimate)}")
def area_under_curve_estimator(
iterations: int,
function_to_integrate: Callable[[float], float],
min_value: float = 0.0,
max_value: float = 1.0,
) -> float:
"""
An implementation of the Monte Carlo method to find area under
a single variable non-negative real-valued continuous function,
say f(x), where x lies within a continuous bounded interval,
say [min_value, max_value], where min_value and max_value are
finite numbers
1. Let x be a uniformly distributed random variable between min_value to
max_value
2. Expected value of f(x) =
(integrate f(x) from min_value to max_value)/(max_value - min_value)
3. Finding expected value of f(x):
a. Repeatedly draw x from uniform distribution
b. Evaluate f(x) at each of the drawn x values
c. Expected value = average of the function evaluations
4. Estimated value of integral = Expected value * (max_value - min_value)
5. Returns estimated value
"""
return mean(
function_to_integrate(uniform(min_value, max_value)) for _ in range(iterations)
) * (max_value - min_value)
def area_under_line_estimator_check(
iterations: int, min_value: float = 0.0, max_value: float = 1.0
) -> None:
"""
Checks estimation error for area_under_curve_estimator function
for f(x) = x where x lies within min_value to max_value
1. Calls "area_under_curve_estimator" function
2. Compares with the expected value
3. Prints estimated, expected and error value
"""
def identity_function(x: float) -> float:
"""
Represents identity function
>>> [function_to_integrate(x) for x in [-2.0, -1.0, 0.0, 1.0, 2.0]]
[-2.0, -1.0, 0.0, 1.0, 2.0]
"""
return x
estimated_value = area_under_curve_estimator(
iterations, identity_function, min_value, max_value
)
expected_value = (max_value * max_value - min_value * min_value) / 2
print("******************")
print(f"Estimating area under y=x where x varies from {min_value} to {max_value}")
print(f"Estimated value is {estimated_value}")
print(f"Expected value is {expected_value}")
print(f"Total error is {abs(estimated_value - expected_value)}")
print("******************")
def pi_estimator_using_area_under_curve(iterations: int) -> None:
"""
Area under curve y = sqrt(4 - x^2) where x lies in 0 to 2 is equal to pi
"""
def function_to_integrate(x: float) -> float:
"""
Represents semi-circle with radius 2
>>> [function_to_integrate(x) for x in [-2.0, 0.0, 2.0]]
[0.0, 2.0, 0.0]
"""
return sqrt(4.0 - x * x)
estimated_value = area_under_curve_estimator(
iterations, function_to_integrate, 0.0, 2.0
)
print("******************")
print("Estimating pi using area_under_curve_estimator")
print(f"Estimated value is {estimated_value}")
print(f"Expected value is {pi}")
print(f"Total error is {abs(estimated_value - pi)}")
print("******************")
if __name__ == "__main__":
import doctest
doctest.testmod()
| """
@author: MatteoRaso
"""
from math import pi, sqrt
from random import uniform
from statistics import mean
from typing import Callable
def pi_estimator(iterations: int):
"""
An implementation of the Monte Carlo method used to find pi.
1. Draw a 2x2 square centred at (0,0).
2. Inscribe a circle within the square.
3. For each iteration, place a dot anywhere in the square.
a. Record the number of dots within the circle.
4. After all the dots are placed, divide the dots in the circle by the total.
5. Multiply this value by 4 to get your estimate of pi.
6. Print the estimated and numpy value of pi
"""
# A local function to see if a dot lands in the circle.
def is_in_circle(x: float, y: float) -> bool:
distance_from_centre = sqrt((x ** 2) + (y ** 2))
# Our circle has a radius of 1, so a distance
# greater than 1 would land outside the circle.
return distance_from_centre <= 1
# The proportion of guesses that landed in the circle
proportion = mean(
int(is_in_circle(uniform(-1.0, 1.0), uniform(-1.0, 1.0)))
for _ in range(iterations)
)
# The ratio of the area for circle to square is pi/4.
pi_estimate = proportion * 4
print(f"The estimated value of pi is {pi_estimate}")
print(f"The numpy value of pi is {pi}")
print(f"The total error is {abs(pi - pi_estimate)}")
def area_under_curve_estimator(
iterations: int,
function_to_integrate: Callable[[float], float],
min_value: float = 0.0,
max_value: float = 1.0,
) -> float:
"""
An implementation of the Monte Carlo method to find area under
a single variable non-negative real-valued continuous function,
say f(x), where x lies within a continuous bounded interval,
say [min_value, max_value], where min_value and max_value are
finite numbers
1. Let x be a uniformly distributed random variable between min_value to
max_value
2. Expected value of f(x) =
(integrate f(x) from min_value to max_value)/(max_value - min_value)
3. Finding expected value of f(x):
a. Repeatedly draw x from uniform distribution
b. Evaluate f(x) at each of the drawn x values
c. Expected value = average of the function evaluations
4. Estimated value of integral = Expected value * (max_value - min_value)
5. Returns estimated value
"""
return mean(
function_to_integrate(uniform(min_value, max_value)) for _ in range(iterations)
) * (max_value - min_value)
def area_under_line_estimator_check(
iterations: int, min_value: float = 0.0, max_value: float = 1.0
) -> None:
"""
Checks estimation error for area_under_curve_estimator function
for f(x) = x where x lies within min_value to max_value
1. Calls "area_under_curve_estimator" function
2. Compares with the expected value
3. Prints estimated, expected and error value
"""
def identity_function(x: float) -> float:
"""
Represents identity function
>>> [function_to_integrate(x) for x in [-2.0, -1.0, 0.0, 1.0, 2.0]]
[-2.0, -1.0, 0.0, 1.0, 2.0]
"""
return x
estimated_value = area_under_curve_estimator(
iterations, identity_function, min_value, max_value
)
expected_value = (max_value * max_value - min_value * min_value) / 2
print("******************")
print(f"Estimating area under y=x where x varies from {min_value} to {max_value}")
print(f"Estimated value is {estimated_value}")
print(f"Expected value is {expected_value}")
print(f"Total error is {abs(estimated_value - expected_value)}")
print("******************")
def pi_estimator_using_area_under_curve(iterations: int) -> None:
"""
Area under curve y = sqrt(4 - x^2) where x lies in 0 to 2 is equal to pi
"""
def function_to_integrate(x: float) -> float:
"""
Represents semi-circle with radius 2
>>> [function_to_integrate(x) for x in [-2.0, 0.0, 2.0]]
[0.0, 2.0, 0.0]
"""
return sqrt(4.0 - x * x)
estimated_value = area_under_curve_estimator(
iterations, function_to_integrate, 0.0, 2.0
)
print("******************")
print("Estimating pi using area_under_curve_estimator")
print(f"Estimated value is {estimated_value}")
print(f"Expected value is {pi}")
print(f"Total error is {abs(estimated_value - pi)}")
print("******************")
if __name__ == "__main__":
import doctest
doctest.testmod()
| -1 |
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